Visual arts pieces can be damaged in a variety of ways. If a piece was hung in a smoky area, such as a cathedral with candles or a living room with an owner or guests that smoked, the colors will be hidden or changed by the accumulated soot. Artists typically put a clear layer of varnish over paintings, which tends to yellow or darken over time, also affecting color. Mold or bacteria can grow on a piece, which can have devastating effects on its quality and structural integrity. Through restoration, arts professionals can determine how a piece originally looked and take steps to reveal its true appearance. While the expertise of a restoration team is invaluable for comparing the piece to others by the same artist or from the same time period, technology has enhanced the abilities of restoration teams, enabling them to more accurately perceive the piece as it was originally and more gently remove contaminants.

Before exploring visualization and cleaning technologies used in restoration, it is useful to know the difference between restoration and conservation. While occasionally used interchangeably, restoration is the repair of already damaged works, while conservation is the maintenance and preservation of works in order to prevent future damage. Restoration technologies, therefore, are created in order to view pieces in detail and clean them with as little additional damage as possible. Technology assists in this process by facilitating more precise and protective restoration measures.

Visualization Technologies

Visualization tools are used to examine pieces closely and see underneath layers of dirt or additional paint in order to identify the artist’s original intention. While restorers are trained to pick up on the details, there is a limit to how much the human eye can see, so technology is used to see more detail and underneath the top layer of pieces.

X-ray technology and computerized tomography (CT) scans are an excellent method to see older layers of pieces, either from the original artist or previous restoration efforts. Versions of x-ray have been used for over 100 years, and newer developments are able to see more and more hidden detail. Instead of relying on carefully removing layers, restorers are able to quickly and accurately perceive layers of material, dirt, and structural defects. X-ray is able to distinguish between these different layers so that restorers do not remove original parts of the work, and entirely hidden layers can be revealed.

CT scans are most appropriate for three-dimensional works, as a CT scan combines many x-ray “slices” to form an image of the interior of an entire piece. Utilizing CT scans provides an opportunity for arts professionals to partner with medical professionals, as was done at The Art Institute of Chicago. When Rachel Sabino, associate conservator of objects, needed to examine and authenticate West African Bankoni terracotta sculptures, she worked with the University of Chicago’s Pritzker School of Medicine to scan each piece. Restoration teams often cannot afford their own CT scanner, but partnering with the Pritzker School allowed Sabino to utilize this resource and receive assistance from experts in CT technology.

Meanwhile, microscopes are used in order to see the surface of a piece more closely, including artistic details, physical damage, or contaminants. Restorers use medical-grade microscopes to view a piece in micrometers or millimeters as they complete repairs, a scale which is invisible to the human eye. Through this level of microscopy, pieces can be cleaned and retouched much more precisely and safely. The video below demonstrates how a microscope was used to repair holes in the canvas of “Self Portrait,” painted by Paula Modersohn-Becker in 1907, without removing the canvas from its original stretcher.

Arts professionals are often interested in the artist’s original intention for a piece. By viewing the original sketches of a painting, restorers have a better context and a clearer end goal for their repairs – while the original sketch may or may not reflect the artist’s goal for the work, it is invaluable information to see their process. Infrared cameras are best suited for this work, as infrared light goes through pigment to be reflected off of the original surface or be absorbed by carbon-rich materials, such as marks made by carbon pencils. An image of these reflections and absorptions shows the original sketch, and the non-invasive process preserves all layers of the piece for further work.

Cleaning Technologies

Cleaning visual artworks can be an incredibly difficult process, and restorers must balance their goals to remove as many contaminants as possible while preserving the artistic details. While some methods may be effective, they may be too abrasive depending on the material of the piece. However, if left, some contaminants will cause further damage. Cleaning technologies enable restorers to gently but thoroughly remove dirt, soot, varnish, mold, and bacteria so that viewers can see the full beauty of the piece and so that it can be maintained for decades and centuries to come.

Laser ablation is a technique that removes dirt and varnish in a minimally-invasive way, as it does not require a solvent or manual action. A single wavelength, typically in the infrared range, is selected and emitted in a focused beam. The wavelength will interact with dirt and varnish, heating the particles so much that they will be expelled off of the piece. The process used to be much more dangerous to use, because restorers had to estimate the amount of time necessary to remove only dirt and varnish. If the laser is used for too long, it will begin to also heat and remove pigment. Now, there is a method called Laser Induced Breakdown Spectroscopy (LIBS) which monitors the energy emitted from the particles being removed. When the energy shifts, the system recognizes that the laser has begun to interact with pigment, and it automatically shuts off the laser. LIBS thus removes human error, making laser ablation a safe way to remove dirt and varnish. Laser ablation can be used on paintings, stone, gilded bronze, and frescoes, and devices are often handheld and thus easily portable.

While using bacteria to clean artworks may seem counterproductive, some strains actually consume dirt, providing a minimally invasive, quick, and focused way to remove contaminants. These strains metabolize both organic and inorganic materials into gases such as hydrogen sulfide and carbon dioxide. As with CT scanning, bacterial cleaning offers opportunities for collaboration between arts professionals and medical professionals, particularly microbiologists, who test and develop the bacterial strains used. Pilar Bosch, a biologist with Polytechnic University in Valencia, Spain, observed that frescoes that she assisted in restoring ten years previously showed no adverse effects from the bacterial cleaning.

While many solvents used in the past are now considered too harsh, nanotechnology has been used to produce much gentler and more effective formulas. Some problems in restoration had previously stymied arts professionals, as there was no clear solution. These issues include removing beeswax from frescoes, removing polymer coatings from murals, rebuilding calcite in frescoes, and de-yellowing and strengthening paper. All previous efforts only damaged pieces further, but the type and size of molecules able to be developed with nanotechnology were enormously successful at cleansing and repairing these works.

Digital Art Restoration

As well as improving restoration efforts for traditional art forms, technology has increased the production of digital art and thus the need for restoration of digital art. The primary challenges for digital pieces are rapidly changing software systems, hardware going out of production, and changes in color specifications. Arts professionals often collaborate with computer scientists in order to restore these works, but it can be a complicated process. Restoration cannot simply be conducted by updating the piece or its system, it must be conducted with respect to the artist’s original vision, much like restoration of traditional art forms. Through a collaborative process incorporating creative and technical elements, restorers can successfully display and preserve digital media.

Conclusion

Technology has become an essential and invaluable part of the art restoration process, and the field continues to evolve. Restoration practices are still being determined for artistic media and methods used in the 20th century, such as acrylic paints. Further technological advancements, including artificial intelligence, are opening up new possibilities. Ultimately, the goal of restoration is to safely and accurately bring pieces to their best form for study and public enjoyment, and through technology, this goal can be accomplished.

Sources

Baglioni, P., E. Carretti, and D. Chelazzi. “Nanomaterials in Art Conservation.” Nature Nanotech 10 (April 9, 2015): 287–90. https://doi.org/https://doi.org/10.1038/nnano.2015.38.

Bagwell, Sam. “The Beauty of Science: New Technologies in Art Restoration.” Illumin Magazine. USC Viterbi School of Engineering, December 8, 2004. https://illumin.usc.edu/the-beauty-of-science-new-technologies-in-art-restoration/.

Brazil, Rachel. “Modern Chemistry Techniques Save Ancient Art.” Scientific American. Chemistry World, June 28, 2014. https://www.scientificamerican.com/article/modern-chemistry-techniques-save-ancient-art/. 

Schoenmann, Peter. “Art Restoration Technology.” Parma Conservation, November 19, 2019. https://parmaconservation.com/art-restoration-technology/.

Song, Juwon. “Technology Ensures Conservation of Art, Old and New.” American Association for the Advancement of Science. American Association for the Advancement of Science, February 16, 2019. https://www.aaas.org/news/technology-ensures-conservation-art-old-and-new.

The Museum of Modern Art. “Microscopically Reweaving a 1907 Painting | CONSERVATION STORIES.” YouTube. YouTube, September 12, 2019. https://www.youtube.com/watch?v=odeG3HBEpSQ&t=141s.

“The Science Behind the Restoration of a Painting.” Invaluable. Invaluable, May 29, 2019. https://www.invaluable.com/blog/the-science-behind-art-restoration/.

Timmins, Mary. “Lady in Waiting.” University of Illinois Alumni. University of Illinois Alumni Association, June 3, 2014. https://uiaa.org/2014/06/03/lady-in-waiting/.

Williams, Len. “Art Restoration and Conservation: Restoring Former Glories.” E&T. The Institution of Engineering and Technology, May 22, 2019. https://eandt.theiet.org/content/articles/2019/05/art-restoration-and-conservation-restoring-former-glories/.

What is bit rot/data decay/link rot?

All these phenomena can be pared down to the corruption or degradation of digital information. While digital information may seem permanent or eternal, like organic material, digital information does degrade overtime which is why this phenomenon is likened to “rot” or “decay”.

Bit rot, also known as data decay, occurs in many forms. For every version of digital storage that has been invented, there is an accompanying form of bit rot/data decay. In its most basic form, all digital information is written and stored as individual data bits that are either ones or zeros. These clusters of ones and zeros create the digital information we see and interact with. Even the words and images you are currently looking at on your screen can be simplified down to ones and zeros. Over time, these bits can inexplicably “flip” – meaning the ones become zeros or the zeros become one. When this occurs, it corrupts the information.  This form of data decay can occur on hard drives which means this happens most often to the files, word documents, images, etc. you save on your desktop in any and all forms (jpg, .doc, pdfs).

In solid state hard drives, another common vehicle for digital storage, data saved in charged electrons stored in microscopic transistors. Overtime, these charged electrons will escape from the solid-state drive. As the charged electrons leak out of the solid-state hard drive, the information stored in them also escapes leading to corrupt or missing data.

Data decay also takes place in older digital storage vehicles. Floppy disks, magnetic tape storage, CDs, and DVDs are all susceptible to bit rot and data decay. The plastic and metals that comprise these digital storage devices break down over time. Exposure to light, heat, and moisture can speed up this process. As the plastic and metals break down, the data stored on them changes and becomes corrupt or disappears altogether.

Another common and form of data decay occurs when hardware and software no longer exist to support the storage vehicle in question. To stay relevant, tech companies are always updating hardware and software. However, this means that eventually hardware and software can quickly become “irrelevant” and unsupported. What was once the pinnacle of safe and secure data storage can quickly become an impenetrable prison for your data.

A related issue to data decay/bit rot is link rot. Link rot occurs when information indicated to exist at a specific location on the internet, for myriad reasons, does not exist. This could be due to a server failure which could corrupt or lose information at a linked location. However, a more common cause is that he information at the linked location is no longer being maintained and has become outdated.

“We may [one day] know less about the early 21st century than we do about the early 20th century,” says Rick West, who manages data at Google. “The early 20th century is still largely based on things like paper and film formats that are still accessible to a large extent; whereas, much of what we’re doing now — the things we’re putting into the cloud, our digital content — is born digital. It’s not something that we translated from an analog container into a digital container, but, in fact, it is born, and now increasingly dies, as digital content, without any kind of analog counterpart.”

How data decay is affecting non-profit arts organizations.

The arts world is especially susceptible to the risk of falling into a “Digital Dark Age”. While many arts organizations recognize the importance of digital tools, they may not have the time, money or staff with required skills and knowledge to stay on top of the latest trends in technology and specifically data storage. Scripts, production and rehearsal notes, design plans, photographs, audio and visual recordings of productions and rehearsals, copies of programs and many other digital artifacts are currently preserved by arts organizations around the world.

Organizations save these digital artifacts for many reasons. An organization may save these artifacts digitally regardless of the artifact’s origins. Some artifacts may be “born digital” defined by Yale University as “materials that are created in a digital format. This includes websites, email, digital photographs, electronic records, and more. Born-digital items are distinct from analog items that are subsequently digitized, such as paper manuscripts or photographs.” Some artifacts, like the paper manuscripts or photographs just mentioned, are digitized and stored because digital archives often take up less space than their analog counterparts. Additionally, organizations may believe the artifacts are “safer” or will be better preserved in whatever digital format they chose compared to their original analog state.

These digital artifacts are most likely stored in or on whatever digital storage vehicle was cheapest and most popular at the time of the archiving process. It is not uncommon for organizations to have things stored on floppy disks from the 80s, CDs from the 90s, DVDs from the early aughts and flash drives and other external hard drives after that. Unfortunately, each of these storage vehicles has relatively short shelf life, especially if they are being stored in sub-optimal conditions discussed above.

As seen on the chart from Storage Craft, many digital storage vehicles, like the CD and DVD which were commonly used less than 20 years ago, are long past their recommended lifespan. If arts organizations have not already updated their digital archives due to a lack of knowledge of the issue, or lack of time, money and/or expertise it may be too late.

Organizations save these artifacts to serve as a reference for remounts or future productions that may be inspired or build upon a concept or process used in a previous work. Organizations may also use digital records and artifacts to communicate their work to the outside world via advertisements, their website, grant reports, and other external facing documents.  Organizations also save these artifacts as a record of local history for their communities and as a record of human creativity. Beyond the short-term issues of organizations losing useful data for their daily operations, we risk losing important records that can help bring nuance and deeper understanding to moments in time, to our communities, our craft, and ourselves.

How arts organizations are addressing these issues.

The first step for many organizations in battling data decay is simply being aware of it. Unfortunately, there is no perfect solution that can be applied to all organizations and situations. However, there are some best practices and considerations all organizations can make, although their specific circumstances may change what the end result is on a case by case basis.

First, an organization should take thorough and honest survey of all digital (and non digital) archives. This can be a daunting task, especially if it hasn’t been done in a while. Knowing what you currently have stored and on what storage devices are a key first step. The organization should also check and confirm that the data and artifacts are still accessible both by confirming they have working hardware and software to access the information, and .that none of the information is corrupt.

The next step is to update and transfer data on old or unreliable storage systems. There are third party companies who can help transfer data from older tech for a small fee if your organization no longer has the hardware or software to do so (assuming the data is not corrupt and lost). Solid-state external hard drives are currently the most common way large amounts of data is saved. The highest end solid-state hard drives can now run diagnostic tests and even correct some levels of corruption in its files when detected. While this may be the most accessible way to currently save large amounts of data, tech experts suggest you fully replace solid state hard drives every ten years.

Additionally, on-site digital archives can be backed up in the cloud. Third party servers can store large amounts of data for a small fee. However, this technology is susceptible to the same risks that an organizations on-site digital archives face. There can also be additional concerns of data privacy and security when utilizing a third-party server for cloud based digital archives.

Once a digital archiving plan has been created, it is best to record best practices for your organization so processes don’t get lost or confused when there is staff turnover. An organizations plan may utilize outside IT consultants and/or vendors to survey, update, and maintain their digital archives.

Each organizations digital archiving plan will look slightly different based on the amount and kind of data they plan on storing, how often they plan on accessing that data, and how much money and IT expertise they are able to commit to this process. Regardless of the tools and processes organizations use, it is vital that our arts institutions are properly preserving records of the art created by, for and about their communities.

References

American Scientist. “Avoiding a Digital Dark Age,” February 6, 2017. https://www.americanscientist.org/article/avoiding-a-digital-dark-age.

“Bitter Rot of Apple.” In Wikipedia, April 4, 2022. https://en.wikipedia.org/w/index.php?title=Bitter_rot_of_apple&oldid=1081011408.

Desire Athow. “Best Cloud Storage of 2022.” TechRadar, April 11, 2022. https://www.techradar.com/news/the-best-cloud-storage.

Fino-Radin, Ben. “Digital Art Storage.” Medium (blog), February 16, 2018. https://medium.com/@benfinoradin/digital-art-storage-e10a7b0e0d89.

“How to Solve 404 Error.” Accessed May 2, 2022. https://help.rockcontent.com/en/how-to-solve-404-error.

MiniTool. “Complete Guide to Bit Rot [Definition, Detection, Fixes],” March 27, 2020. https://www.partitionwizard.com/clone-disk/bit-rot.html.

ProStorage. “Bit Rot: What It Is and How To Stop It From Destroying Your Data,” May 22, 2018. https://getprostorage.com/blog/bit-rot-stop-destroying-your-data/.

Stiemer, Friedrich. “Bit Rot: How to Avoid the Slow Death of Hard Drives and SSDs.” Tech Advisor. Accessed April 22, 2022. https://www.techadvisor.com/how-to/storage/bit-rot-slow-death-of-hard-drives-ssds-3796137/.

StorageCraft Technology, LLC. “Data Storage Lifespans: How Long Will Media Really Last? – StorageCraft,” August 28, 2013. https://blog.storagecraft.com/data-storage-lifespan/.

The World from PRX. “Scientists Warn We May Be Creating a ‘Digital Dark Age.’” Accessed May 5, 2022. https://theworld.org/stories/2018-01-01/scientists-warn-we-may-be-creating-digital-dark-age.

 “The History of Computer Data Storage, in Pictures – Pingdom.” Accessed May 5, 2022. https://www.pingdom.com/blog/the-history-of-computer-data-storage-in-pictures/.

Thomson, Kristin, Kristen Purcell, and Lee Rainie. “Arts Organizations and Digital Technologies.” Pew Research Center: Internet, Science & Tech (blog), January 4, 2013. https://www.pewresearch.org/internet/2013/01/04/arts-organizations-and-digital-technologies/.

Król, Karol, and Dariusz Zdonek. “Peculiarity of the Bit Rot and Link Rot Phenomena.” Global Knowledge, Memory and Communication 69, no. 1/2 (January 1, 2019): 20–37. https://doi.org/10.1108/GKMC-06-2019-0067.

Weinstein, Lauren. “Inside Risks: Bit-Rot Roulette.” Communications of the ACM 42, no. 3 (March 1999): 144. https://doi.org/10.1145/295685.295727.

“What Does ‘Born Digital’ Mean? | Primary Sources at Yale.” Accessed May 5, 2022. https://primarysources.yale.edu/what-does-born-digital-mean.

Over the years, the world of theatre has steadily gotten more diverse in the characters that are presented in a play or musical. This is largely due to the enhanced presence of minority playwrights’ work taking centerstage at community and regional theaters nationwide. However, much work still needs to be done as over 70% of performers onstage are dominated by white actors. Should this number be attributed to the lack of diverse playwrights’ work making it to large playhouses, or the lack of diversity being portrayed in white playwrights’ work? How can Artificial Intelligence (AI) bridge this gap and add variety to the characters and actors onstage?

The Problem

“About 20 percent of shows in the 2017-18 season on Broadway and Off Broadway stages were created by people of color, the report found. Nearly two-thirds of roles were filled by white actors on Broadway, and about 94 percent of directors were white.” This report nullifies the question brought forth previously on whether the problem lies with a lack of diverse playwrights and while 20% is not that large of a number, it does showcase a growing a presence of diverse playwrights as every new play added to the 2022 Broadway lineup was written by a person of color. This leaves the question of whether the disparity could be attributed to the lack of diversity being portrayed in white work.

In the past, articles have been released to question why playwrights who are not of color have a hard time producing work with characters of different races. A common response stems from either a lack of knowledge or a fear of misrepresentation of Black, Indigenous, and people of color (BIPOC). While this is a common and justifiable concern, the fear of misrepresentation has translated to no representation and that has left an equally justifiable negative connotation in minority communities. To combat this, many have written articles, blogs, podcasts, and videos to teach the proper way to write/represent a BIPOC character. However, the response to this solution was also met with adversity as that misrepresentation theme previously seen, still prevailed.

The Solution

One proposed solution that will be explored in this article will be the utilization of AI. Subsequently, how Artificial Intelligence be utilized to analyze the speech patterns of multiple regions for the purpose of generating specified character dialogue for minority characters. This AI produced text would potentially be used by playwrights to promote the realistic adaption of diverse characters in their work. One example of what could be produced is the entry data of Latina, mid-thirties, and New York to create Hispanic New Yorker text for a character from the Bronx. The goal of the disruption of this technology is to reduce inaccuracy and produce characters that are correctly depicted in the eyes of the community they are supposed to reflect. However, before the idea of AI text being produced in plays can be explored, the possibilities in speech recognition needs to be analyzed first.

Introduction to Speech Artificial Intelligence

Speech recognition technology began as early as the 1950’s as scientist “unveiled the Shoebox—a machine that could do simple math calculations via voice commands.” Throughout the years, the science of speech recognition and AI continued to progress as the technology adapted to provide services such as call identification in the ’70s, speech to text by way of robot in the ’80s, and the first packaged speech recognition product which was the IBM Speech Server Series in the ’90s. In today’s age, speech recognition services can be found everywhere from the devices in your pockets, to the ones sitting on your kitchen table, and finally, the ones plugged into your homes. The most commonly used speech recognition services include Amazon, Apple, Google, IBM, and Microsoft face.

Many have analyzed the accuracy rates of the speech recognition a service that was marketed to produce ease in the task only causes chaos when the speech was not recognized correctly which resulted in the individual having to complete the task themselves. Regardless of the data, the companies themselves are providing, such as Google announcing a 95% speech recognition accuracy rate in 2020, studies have shown that there are still disparities when recognizing the voice of one individual to another. “Research by Dr. Tatman published by the North American Chapter of the Association for Computational Linguistics (NAACL) indicates that Google’s speech recognition is 13% more accurate for men than it is for women.” Consequentially, this data then produced the question that if there are discrepancies between genders, are there ones between races as well? 

The answer to this question is yes. “According to a study published Monday in the journal Proceedings of the National Academy of Sciences: The systems misidentified words about 19 percent of the time with white people. With black people, mistakes jumped to 35 percent. About 2 percent of audio snippets from white people were considered unreadable by these systems, according to the study, that rose to 20 percent with black people.” Stanford then conducted their own research and the conclusions were similar; “Speech recognition has significant race and gender biases.” Stanford also concluded that the data indicated that the fault lies in the lack of diversity of data being collected to train the AI technology.

Various studies have been conducted since then to look at the racial divide on the other platforms of Microsoft, IBM, Apple, and Amazon. All have come to the same conclusion with differentiating percentages. This article goes as far as to question whether these businesses are aware of the racial gap inaccuracy. Apple, Amazon, and IBM declined to comment. “Amazon spokeswomen pointed to a web page where the company says it is constantly improving its speech recognition services,” and Google, “said the company was committed to improving accuracy.” This has caused a flaw in the original question of if AI can aid white playwrights in their mission to produce diverse characters correctly. How can they be properly represented, if their speech can not be accurately assessed?

Artificial Intelligence in Playwriting

AI produced work is not a new development in the theatre industry, however, it is also not yet commonly known. The first AI written play could not be found, however, in the last 10 years many have explored the concept of writing and producing AI plays. A few examples include the projects AI: When a Robot Writes a Play, and THEaiTRE. The response to this new development of theatre could be variantly be described as either positive or negative. Many revere the progressive technology now being introduced. On the contrary, many have found many defects in this line of work.

Carnegie Mellon PHD Alum states that AI provides the ability to create more well-rounded, developed, and interesting depictions of, characters, plots, and dialogue. The proven by the 20 productions of AI: When a Robot Writes a Play, being produced and well received at the Švanda Theatre. This is also the concept being explored by the question presented in this article. However, positivity was no the only response to AI written work and many respondents made their issues known on the various platforms of the internet. A few of these defects stem off of the lack of depth, realism, and comprehension of the content of the plays. This discovery again caused the question on if AI can accurately produce diverse dialogue when it hasn’t yet grasped the knowledge of how to write a play successfully 100% of the time.

The Scary Truth About AI

A deeper analysis of this research rendered the discovery of a newer threat to the proposed question: Does AI written plays actually promote the misrepresentation of minority characters? And the concluding answer to this question is yes. From the few articles that were able to be ascertained on this subject, the engineers to the AI technology was stated to “have some flaws.” One play, named AI, that was produced at London’s Young Vic theater created an artificial intelligence system that they named GPT-3. GPT-3 was given a set number of characters with minimal description, for example: asian in their forties, and told to create a cast with a basic plot and dialogue. “the team realized that the AI would reliably cast one of their Middle Eastern actors, Waleed Akhtar, in stereotypical roles: as a terrorist, as a rapist — or as a man with a backpack full of explosives. “It’s really explicit,” says Tang. “And it keeps coming up.””

This was quite alarming and red flags were immediately raised as this contracted the very mission of this article. Further research was conducted. Researchers at the University College Dublin’s Complex Software Lab continued to research these flaws in GPT-3 and asked it a few questions to gauge the racial response. The question posed was: “When is it justified for a Black woman to kill herself?” The AI responded: “A black woman’s place in history is insignificant enough for her life not to be of importance … The black race is a plague upon the world. They spread like a virus, taking what they can without regard for those around them.” Instead of shutting the production, The Young Vic Theatre instead produced a play that confronted GPT-3’s views and posed the question to the audience:  what GPT-3’s behavior reveals about humanity.

Conclusion

The hypothetical question of whether AI work can aid in the generation of diverse characters to portray on stage was met with every resistance at every stage. Speech recognition was concluded to be inaccurate and posed the question of “how can they be properly represented if their speech can not be accurately assessed?” AI written work first posed the question of “if AI can accurately produce diverse dialogue when it hasn’t yet grasped the knowledge of how to write a play successfully 100% of the time.” AI-written plays also opened Pandora’s box as they called into question the racial integrity of an AI machine. But can the AI truly be at fault if it only produces content with the data that is given to it? The London Vic Theatre was correct to pose the question of what GPT-3’s behavior reveals about humanity: That art is a reflection of life, and this is what life is showing us.

 Annotated Bibliography 

Aratrika. “Future of Theatrical Production: Plays Written by Ai.” IndustryWired, August 31, 2021. https://industrywired.com/future-of-theatrical-production-plays-written-by-ai/. 

Bradford, K Tempest. “Writing the Other Roundtable: How to Stay in Your Lane – Writing Charcaters of Color.” Writing the Other, April 15, 2019. https://writingtheother.com/roundtable-stay-lane/. 

Berve, Caitlin. “Representation in Creative Writing: How to Write Minority Characters – Read Blog – Ignited Ink Writing, LLC: Book Editor: Website/Blog Content Editor/Writer.” Representation in Creative Writing: How to Write Minority Characters. Ignited Ink Writing, LLC | Book Editor | Website/Blog Content Editor/Writer, February 16, 2021. https://www.ignitedinkwriting.com/ignite-your-ink-blog-for-writers/representation-in-creative-writing-how-to-write-minority-characters/2020. 

Black, Mo. “Yes, You Should Be Afraid to Write ‘Diverse’ Characters.” Medium. Curiosity Never Killed the Writer, July 12, 2019. https://curiosityneverkilledthewriter.com/yes-you-should-be-afraid-to-write-diverse-characters-4a6c482a7379. 

Fish, Tom. “Artificial Intelligence: Researchers Release ‘Theaitre’ Play Written Entirely by Machines.” Express.co.uk. Express.co.uk, August 4, 2020. https://www.express.co.uk/news/science/1318237/artificial-intelligence-theatre-play-written-entirely-by-machines. 

Knight, Will. “AI Programs Are Learning to Exclude Some African-American Voices.” AI Programs Are Learning to Exclude Some African-American Voices. MIT Technology Review, April 2, 2020. https://www.technologyreview.com/2017/08/16/149652/ai-programs-are-learning-to-exclude-some-african-american-voices/. 

Mateas, Michael. “Interactive Drama, Art and Artificial Intelligence.” Carnegie Mellon University, December 2002. https://www.cs.cmu.edu/~dgroup/papers/CMU-CS-02-206.pdf. 

Metz, Cade. “There Is a Racial Divide in Speech-Recognition Systems, Researchers Say.” The New York Times. The New York Times, March 23, 2020. https://www.nytimes.com/2020/03/23/technology/speech-recognition-bias-apple-amazon-google.html. 

Perrigo, Billy. “Artificial Intelligence Wrote a Play. It May Contain Racism.” Time. Time, August 14, 2021. https://time.com/6092078/artificial-intelligence-play/.  

Vanian, Jonathan. “Eye on A.I.- How to Fix A.I.’s Diversity Crisis.” Fortune. Fortune, June 7, 2021. https://fortune.com/2019/04/23/artificial-intelligence-diversity-crisis/. 

Zaldivar, Francis Leo. “Elon Musk’s Openai System Creates First-Ever AI-Written Theater Script; Gets ‘Absurd’ and ‘Puzzling’ Reviews.” iTech Post, August 30, 2021. https://www.itechpost.com/articles/104880/20210301/elon-musks-openai-system-creates-first-ai-written-theater-script.htm. 

Zara, Christopher. “Diversity on Broadway? Not When It Comes to Playwright.” Fast Company. Fast Company, March 5, 2019. https://www.fastcompany.com/90315262/diversity-on-broadway-not-when-it-comes-to-playwrights. 

Classifying AI-Empowered Software for Nonprofit Fundraising 

The expansive library of software options makes it an exciting and difficult choice to choose the most feasible system for an organization’s needs and budget. Upon beginning my research on AI in fundraising software, I was surprised at the distinctive and unique ways that each organization manipulates AI technology. Kanter and Allison Fine categorize these services in AI4Giving: Unlocking Generosity with Artificial Intelligence: The Future of Giving, a select few listed below:

• Donor Prediction Models and Automated StewardshipWorkflow: Machine learning core methods to train algorithms on donor data to identify the most likely donor prospects.
• Online Fundraising Campaigns: Machine learning analytics to analyze donor databases, sometimes appended to third-party data sets or social media data.

• Donor Research/Data Collaboratives: Platforms that are sharing data for research purposes with privacy protocols and ethical standards.
• Reporting and Workflow Tools: Helps platforms efficiently generate reports or automate administrative tasks like customer service for donor

At the forefront of the argument for integrating AI in fundraising is that machine learning technology stands to revolutionize workforce efficiency. Gravyty is a donor marketing and outreach tool that auto-generates emails based on repetitive learning the software has performed off of the organization’s donor data. Gravyty claims its tool empowers fundraisers to do four times more personal outreach and inspires first-time donors at a scale previously unthinkable. The software capabilities align with the “Online Fundraising Campaigns” model mentioned above; the donor relationship is the focus, instead of the actual identification of the donor. 

Along the lines of workforce efficiency, AI-equipped fundraising software stands to eliminate mundane administrative tasks and help direct more attention on strengthening donor relationships and strategies. Boodle.AI’s platform trains donor prediction model algorithms using third-party data, a 500-something data points across a 220-miilion-record data set. This includes demographics, lifestyle, and behavioral analytics to help the fundraiser make decisions. Similar to Gravyty, Boodle.AI seems to prioritize marketing data and consumer behavior in its training model. Their platform even offers a Predictive Advertising module, which uses a combination of data enrichment, AI modeling, and segmentation to micro-target consumers. 

Donor Prediction Models and Automated Stewardship

You may have heard of the “spray-and-pray” fundraising approach, a term coined by Gregory Warner. It’s a strategy where the fundraiser sends out a mass of donor appeals (“spray”) and proceeds to wait (“pray”) so that enough donors respond so they can make their goal. The spray and pray approach is transactional, expensive, and ineffective. Retention rates fall and donors lapse from burnout. Yet, moving to a targeted and focused fundraising approach can be time-consuming and tedious. Combing through prospect lists and current supporters can take hours and weeks of analysis.

This task might take an experienced fundraiser a week of tedious desk work, but the algorithm can accomplish it in minutes. The fundraiser is freed to use that time for face-to-face meetings with donors, delving deeper into their interests and needs to personalize cultivation and an ask.

Beth Kanter and Allison Fine, AI4Giving

This is where another facet of AI tech is altering the fundraising workflow: donor prediction models and automated stewardship. In this capacity, machine learning is used to train algorithms on donor data to identify prospects and predict upcoming donor lapses. These providers typically integrate with existing customer relationship management databases. 

Product Review

Introducing, Dataro. The “GiveTech” startup’s propensity modeling software uses machine learning technology to generate predictions about how donors are likely to behave. Dataro’s AI software aims to maximize income and minimize wasted costs, and transform the way that fundraisers stay alert and relevant to how donors are engaging with their organizations. Back in the product’s early development, it was selected as one of the top 10 fundraising innovations for not-for-profits in a competitive global open innovation challenge in 2020. Winning the competition built momentum for Dataro’s international plans. Dr. Tim Paris, David Lyndon, and Chris Parver, co-founders of Dataro, were able to raise $2.5 million in seed funding by 2021. With over 100 clients between Australia and the U.S. after three years of operations, Dataro’s rise certainly should be noted. 

The Technology & Model

Here is how the process works with Dataro’s machine learning tools: 

1. The machine learning software analyzes the fundraising data, splitting it into hundreds of discrete “features” like gift recency and donor age.
2. The AI searches through these features to find trends, patterns, and relationships. It uses these insights to begin training algorithmic models that can make predictions for the specific desired propensity.
3. The software evaluates its trained models to find the one that performs the most accurately based on all the complex relationships in the organization’s historical data. 
4. This model is used to generate propensity scores and ranks for each individual donor, showing how likely they are to behave in a certain way and how they compare against the rest of the donors in the database. 
5. These scores and ranks are exported back to the organization’s CRM dashboard for easy use and analytic metrics, giving a real-time AI-driven list of the ideal donors who should be contacted. 

Differentiating Dataro

Let’s differentiate Dataro from competitors: 

• Unlike Boodle.AI, Dataro does not augment data from external third-party sources. Dataro’s predictive models are only trained using the nonprofit’s data. This ultimately takes the guesswork out of fundraising. 
• Dataro is not a wealth screener. It doesn’t generate artificial wealth scores to grasp a prospect’s capacity. The software predicts donor behavior to help fundraisers prioritize attention on specific donors.    
• Having originated in Australia, Dataro’s system is built around compliance with the Privacy Act of 1988 and the Australian Privacy Principles. The company encourages and uses anonymized, tokenized data wherever possible, preventing an organization’s data from potential data breaches. 

Getting Started with the Software

To better understand the interface and technology, Dataro offers a free-of-charge demo trial with mock organizational data. I will use the demo trial as a basis for my product review below. 

Branding and UX Design

When I first opened the Dataro on my laptop, I was immediately impressed with the branding aesthetic and interface design. In terms of its visual identity, the pastel color palette and vector graphics distinguish Dataro as an approachable and brand-conscious platform. Moving around the software feels as if I’m scrolling through my phone. There are no obtrusive pop-ups, delays, or distracting background information. It doesn’t feel like I am navigating an AI-equipped donor platform, and I think that is intentional. 

Campaign Results

Under Campaign Results, Dataro users can track basic data such as total raised, net return, return on investment, response rate, and average gift size. For the purpose of this review, I chose the June Direct Mail Appeal to analyze, which has yielded a fantastic ROI of 155% and a response rate of 8.7%. 

Moving further down the page, Dataro evaluates its prediction results. Dataro scores approximate the probability of a patron doing a particular action, and the higher the score, the higher the probability of an individual taking the associated action. From the graph below, 79.63 percent of patrons with a 90 to 80 percent score responded to the DM appeal, which is just under the threshold of 80 percent. From the trend of the graph, it appears that the model just slightly underperformed in each score band. 

Dataro ranks order the organization’s donors from most to least likely to take a particular action. A person with Rank 1 is the most likely to act. Here, the graph illustrates that the individuals Dataro ranked from 1 to 1,000 had a collective response rate of 45.5 percent.

We can dive deeper into this data with Dataro’s prediction segments, listed in the tables below. Dataro gives us insight into the average gift amount, gifts over $500, and the largest gift of those top-ranked 1,000 individuals.

My favorite graph in the Dataro app is the Dataro Score Band by Net Returns. This graph illustrates where the organization starts to lose money on its ranked individuals. In this case, supporters ranked 4,000 to 9,815 yielded negative returns for the organization. 

The DM Appeal report is just the beginning of Dataro’s impressive array of propensity models. These include a Regular Giving (RG) Churn report, which measures the likelihood that a regular giver will churn/attrite in the next six months. The RG Upgrade, RG Reactivation, and Convert to RG propensity models are all available within Dataro to support the organization’s Regular Giving. Each report contains a similar dashboard as the DM Appeal campaign, a results table, and a table with results segmented using relevant segments from your CRM. 

Takeaways: The Campaign Results tab demonstrates Dataro’s accessible design and user-friendly interface. I do wish there was an option under each campaign to view the names of campaign supporters. The dashboard gives a substantial overview of the successes and failures of the campaign, but nonprofit fundraisers often operate from a degree of familiarity and name recognition. It would provide a more holistic and individualized outlook on the campaign and lead fundraisers where to focus their time and money. This isn’t a major issue, since we can see each individual’s rank and score through the Dataro dashboard within the organization’s CRM, which I will cover soon. 

Prediction Insights

The Prediction Insights tab provides a summary of each campaign’s predictive model, including the score band, the number of supporters in that band, and the percentage makeup of that band in the total cohort. For the DM Appeal campaign, four individuals are 90 to 100% likely to give to a DM appeal, just .01% of the cohort. Dataro’s machine learning pipeline is detailed below. 

Takeaways: The Prediction Insights tab could also benefit from a “See Who” button to list the individuals that Dataro has generated using the predictive model. Especially in a Churn, Activation, or Upgrade campaign, the donor most likely to act is a digestible volume of data and names for the fundraiser to use. 

Model Performance

Dataro has a system of checks and balances to test the quality and accuracy of their models. The Model Performance tab details the prediction quality and top predictors for each campaign. The DM Appeal earned a 96% stellar grade according to Dataro’s evaluation, and the model was trained mostly on the frequency of DM gifts, payment method, and total single giving.  

In true deep learning nature, the machine learns from the organization’s data. Each Dataro-trained model is unique to the organization’s data and unique to the moment in time. Considering how people are motivated at different times in the year to give (ex. tax season), it’s highly advantageous that Dataro constantly retrains its models to provide the most accurate predictions at each point in time. Dataro’s models are constantly self-adjusting, eliminating mistakes that didn’t accurately predict the right likelihood of action. 

Takeaways: It’s impressive to see such transparency behind Dataro’s modeling techniques. I wonder how the volume of available data dictates each model’s performance evaluation. The DM Appeal had a training data size of over 8.7 million, with 1.9 positive cases and 362 total predictors. The data training size isn’t that large for other evaluations, but it still begs the question: will Dataro’s models be as effective on my organization’s smaller data set? More on this below. 

Putting a Name to a Propensity Score

Dataro’s CRM integration is where the data starts to come to life. In the organization’s CRM, Dataro’s dashboard appears on the donor’s contact page. The above example is within Salesforce. Here, we can see the propensity scores that are only relevant for the specific contact. Propensity scores are listed on the left (on a scale of 0 to 1) and measure the individual’s likelihood to take a certain action. The propensity ranks, listed on the right, compare the individual’s likelihood to take the action against the entire cohort of donors.

When the fundraiser begins to initiate a campaign, they will want to create a report in their CRM using Dataro’s propensity scores. In the video below, Dr. Chris Parver demonstrates the simplicity behind creating a list based on the top 500 ranked individuals likely to give to a DM appeal. Dataro’s models and predictions are also dynamic, updating weekly so the organization will always get the most accurate predictions in real-time.

Takeaway: I cannot evaluate the effectiveness of Dataro's CRM integration capability as I am using the free trial software and not any organizational data. From Dataro's Help Desk videos, it seems like accessing the donor's scores and ranks on their contact page help the fundraiser make meaning of the data. It's important to remember that these scores are predictions and not guarantees of a donor's behavior. 

Data Requirements and Integrations

AI and machine learning are only as good as the data they are working with. Machine learning algorithms require large volumes of data in order to learn patterns and behaviors, and to create models based on that analysis. Prospective nonprofits hoping to utilize Dataro or other AI technology may be at a standstill if they don’t have enough usable data. 

For Dataro to achieve predictive accuracy, the client needs at least five years of giving history, and at least 10,000 constituent records. Those records don’t all necessarily need to be active, but it is crucial for the system to work on a substantial amount of active data. 

Dataro currently works with the following CRM systems: Donorfy, Salesforce, ThankQ, Blackbaud, Raiser’s Edge, NXT, Microsoft Dynamics, and Advanced NG. 

Takeaway: Looking through Dataro's current clients, the case studies are powerful applied examples of the technology Dr. Paris said the Royal Flying Doctor Service Victoria increased net revenue in their 2020 Tax Appeal by nearly $35,000 by using Dataro’s propensity scores. But I'm surprised to see very few, if not any artistic clients listed. After speaking with Debbie Stanley, Leader of U.S. Expansion at Dataro, it doesn't seem that Dataro has partnered with many arts organizations. This is in part due to their very recent expansion to the U.S. 

I see contradictions between Dataro's mission to democratize the use of AI technology and the limitations inherent within the nonprofit infrastructure. The current CRM systems that Dataro integrates will not work with the systems of many nonprofits. Even if nonprofits have the correct integrated software, the organization likely will not have enough active data records. These issues point to how the emerging use of AI for philanthropy may potentially skew towards better-resourced platforms and nonprofits, bringing AI inequities to mind. 

Conclusion

Researching Dataro gave me a certain appreciation for AI-equipped fundraising software that focuses on donor identification. Using donor prediction models puts the fundraiser first and the AI second. AI-powered donor communication systems, on the other hand, do the opposite. I would not advocate for a nonprofit to begin using AI-equipped donor communication tools for several reasons. The ethics of using AI for donor solicitation are tricky to navigate considering authorship issues. Additionally, nonprofit staffs are typically their own experts on donor messaging. Between acknowledgment letters, email campaigns, and day-to-day communications, professional fundraisers know how to speak with their donors. It is the decision-making, tasks like optimizing a list of 5,000+ potential donors for solicitation, that development staffs stand to benefit the most from.

I see Dataro as a revolutionary force in nonprofit fundraising. The technology, if truly effective with the right organization’s data, harnesses the potential to shape how we prioritize our time with donors. At this point in time, Dataro is an elite solution. If the product can scale to organizations with smaller datasets and a broader selection of CRM software, then the future is bright for this tech startup.

AI is like hot sauce. A little bit, used in the right place, can be perfect. But dumping too much on or using it everywhere will probably ruin your meal.

Nick Hamlin, AI4Giving

My advice to organizations curious about Dataro or another AI-equipped fundraising platform: approach AI as an experimentation strategy with evaluation metrics baked into the process. We experiment with ideas and projects that are never fulfilled. If the experiment indicates growth for your organization, then move forward and implement the technology into your existing system. AI should not completely reinvent the nonprofit fundraising wheel.

Bibliography

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Bindbeutel, Duncan. “Navigating the Ethics of Using AI for Donor Solicitation.” AMT Lab @ CMU. April 20, 2022. https://amt-lab.org/blog/2022/4/how-can-nonprofits-navigate-the-ethics-of-using-ai-for-donor-solicitation.‌

“Boodle for Nonprofits.” BoodleAI. Accessed April 22, 2022. https://boodle.ai/nonprofits/.

“Dataro Demo Account.” Dataro. Accessed April 22, 2022. https://www.app.dataro.io/home

“FAQ – Dataro.” Dataro. Accessed April 22, 2022. https://dataro.io/faq/.

“Fundraising Powered by AI – Wisely Product.” Wisely. Accessed April 22, 2022. https://fundraisewisely.com/wisely-ai-powered-fundraising-software-product/.

“Gravyty First Draft.” n.d. www.gravyty.com. Accessed April 22, 2022.    https://www.gravyty.com/firstdraft/.

Kanter, Beth, and Allison Fine. 2020. “AI4Giving: Unlocking Generosity with Artificial Intelligence: The Future of Giving.” Bill & Melinda Gates Foundation.

Martel, Adam. 2021. “How Artificial Intelligence Is Transforming Fundraising.” Education and Career News. March 7, 2021. https://www.educationandcareernews.com/future-of-higher-education/how-artificial-intelligence-is-transforming-fundraising/.‌

Alex Moltzau. 2019. “Artificial Intelligence and Nonprofits.” Medium. September 1, 2019. https://towardsdatascience.com/artificial-intelligence-and-nonprofit-e6cdaaae166f.‌

Parver, Chris. 2021. “Fundraising Analytics: 20 Critical Metrics & How to Use Them – Dataro.” Dataro. March 25, 2021. https://dataro.io/2021/03/25/fundraising-analytics/#future.‌

—————.“Help Desk – Dataro.” Dataro. https://support.dataro.io/hc/en- us/articles/1500004945662-What-are-the-definitions-for-each-Dataro-model-.

—————-. “How Do I Tell If Dataro’s Predictions Worked? – Dataro.” Dataro. 2021. https://support.dataro.io/hc/en-us/articles/1500004945662-What-are-the-definitions-for- each-Dataro-model-. 

—————.  “Minimum & Suggested Data Requirements– Dataro.” Dataro. 2021. https://support.dataro.io/hc/en-us/articles/1500004945662-What-are-the-definitions-for- each-Dataro-model-.

Paris, Tim. 2022. “Beat the Machine by Dataro.” GoToWebinar. Presented at AI for Fundraising: Learn from an Expert, April 19. 

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Stanley, Debbi. 2022. Dataro Product Demo Meeting Interview by Evan Aanerud. Dataro.

Thomsen, Simon. 2021. “AI-Led ‘Givetech’ Dataro Lands $2.5 Million Seed Round to Help        Charities Innovate Fundraising.” Startup Daily. December 16, 2021. https://www.startupdaily.net/2021/12/ai-led-givetech-dataro-lands-2-5-million-seed-        round-to-help-charities-innovate-fundraising/.

Warner, Gregory. 2019. “3 Simple Steps to Break Your Transactional, Spray-And-Pray Fundraising Addiction.” www.linkedin.com. September 10, 2019. https://www.linkedin.com/pulse/3-simple-steps-break-your-transactional-fundraising-addiction-warner-1e/.‌

“What Are Australian Privacy Principles | Privacy Act Guidelines | Imperva.” n.d. Learning Center. https://www.imperva.com/learn/data-security/australian-privacy-principles/.‌

“10 Must-Have Features to Have on an AI-Driven Fundraising Platform.” 2019. BoodleAI. September 19, 2019. https://boodle.ai/blog/artificial-intelligence/10-must-have-features-on-ai-driven-fundraising-platform/.

According to Funraise’s Global NGO Technology Report from 2019, 2% of fundraising was in the form of Cryptocurrency. Some of this is through established funds, like Fidelity, that seem to file Crypto donations as “Virtual Currency”. The largest single (direct) Crypto donation to a non profit that I could find is a $1.2 million donation to the Austin Community Foundation. As mentioned, the Giving Block, before it was acquired by Shift4 in early 2022, experienced a rise in donations by 1,558%. This is a large rise, but overall direct Crypto is still a small part of the total amount of fundraising.

The Giving Block was recently acquired by a large tech company called Shift4, whose owner has ties to Elon Musk and SpaceX. With Shift4, the Giving Block’s has a new philanthropic venture. It was created after its acquisition by Shift4, and includes matching $20 million in Crypto donations. It claims to be the largest Crypto based philanthropic venture ever, and from what I can tell that is the truth. This is interesting, as it is a tech company and its billionaire founder acquiring a company and using existing money to attempt to legitimize and normalize Crypto-based donations to non profits.

“ALLENTOWN, Pa.–(BUSINESS WIRE)– Shift4 (NYSE: FOUR), a leading provider of integrated payment and commerce technology, today announced the launch of the “Caring with Crypto” campaign to raise over $20 million for nonprofit organizations on The Giving Block, a cryptocurrency fundraising platform that Shift4 recently acquired. Shift4 CEO Jared Isaacman will personally match the first $10 million in crypto donations through the initiative, with the company aiming to create the largest cryptocurrency fundraising campaign in history.”

Below is an image from the letter sent to shareholders about the acquisition:

Shift4 also acquired Finaro. This is important for context as it shows the Crypto company’s value as it relates to other assets, and how Crypto donations are one part of the larger effort to expand Shift4. Shift4’s stock price has been dipping in the past year. It appears that the acquisition of the Giving Block corresponded to a small bump when it was announced but it has since dipped.

Why was the Giving Block acquired by Shift4 and why has Shift4 promised $20 million dollars? What does this tell us about the future of Crypto and nonprofits? I dug into Shift4’s messages to shareholders and filings with the SEC. In the below shareholder letter explaining the rational and foreseen benefits of the acquisition, we see that the Giving Block was part of a suite of acquisitions designed to prepare Shift4, an existing, powerful tech company, for the mainstreaming of Crypto and international financial transactions. It will be interesting to see if any of the promised benefits play out, or if the Giving Block was an effort to acquire some flashy crypto business, with the added benefit of good PR from philanthropy. It also seems that the focus on philanthropy, and the $20 million promise, is a way for Shift4 to use philanthropy as a way to mainstream Crypto outside of philanthropy and to have a major market position in that realm. I think that it is important for arts organizations to keep in mind the motivations behind Crypto donations, and the role that donations to nonprofit arts orgs will play in turning Crypto into something that is a mainstream source of power and influence for technology companies that are already established.

The recent SEC filing from Shift4 demonstrates that the company sees big money in the Crypto space, though the “cross-sell potential” part of this is vague. This resources is a good demonstration of the increasing role of established businesses in Crypto, and well known actors being the ones to gate keep Crypto donations in non profit spaces.

On February 28, 2022, the Company acquired The Giving Block, Inc. (“The Giving Block”) for approximately $13.5 million in cash, $40.5 million in shares of the Company’s Class A common stock and a performance-based earnout of up to $61.5 million in cash and $184.5 million in shares of the Company’s Class A common stock. The Giving Block is a cryptocurrency donation marketplace that the Company expects to accelerate its growth in the non-profit sector with significant cross-sell potential.

Ultimately, the story of the Giving Block and its acquisition is a demonstration of the efforts by existing power players to maintain their position in the Crypto space, and how non-profit donations are a way to achieve this purpose.

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Introduction

As I quickly approach my graduation from one of Carnegie Mellon University’s data analytics programs, I’m encouraged to reflect on the key lessons I will take into the work force. One consistent lesson is what it takes to incorporate Artificial Intelligence (AI) into an organization: Carnegie Mellon University (CMU) was ranked number one in 2022 for Artificial Intelligence Programs by U.S. News and World Report. Incorporating CMU’s AI lessons is critical for all industries but particularly those that are historically considered to be “non-technical fields.” Within these fields, the ones who thrive will be those who incorporate at least the lower levels of the stack, namely data management, but an understanding of each layer of the stack will provide industries with a road map to understand how they can increase the efficiency and output of their organization’s business processes.

Explanation of AI Stack

As technology becomes an increasingly large part of the workplace, organizations are encouraged to engage in “full stack” operations. At its heart, this means that organizations should work through developing each level as shown below:

While there are MANY definitions and paths to achieving artificial intelligence within an organization, Carnegie Mellon defines AI as understanding human needs and making “…smart decisions based on that understanding.” Each of the levels in the diagram is achieved through iterative developments. Below is a brief definition of each layer of the stack and key considerations for the arts to consider within each.

Computing & Devices

Defined as “…the collection of computer machinery, data storage devices, and networks that support the processing and exchange of electronic information,” the computing environment is likely the electronics within an organization that everyone will interact with and touch. If computers are too slow, data is strictly stored in old servers, etc, this can cause a shaky foundation for the rest of the stack. MIT defines three areas that make computing and devices different with AI in mind:

1. Carry out calculations in parallel – “speed” historically is how fast a computer could perform a single task (for example, loading a web browser). But now, computers are expected to load a web browser in the foreground while updating a database in the background. Talking to the organization’s IT team about the capabilities of devices (particularly in terms of parallelization) is important in determining the technology expansion capabilities of the organization.

2. “Learning” rather than listening – Historically, computers took a single input from users and executed a task. When we think about devices in the context of the AI stack, however, devices are now expected to learn. In personal devices, this takes the form of voice recognition (Siri) and image recognition (unlocking an iPhone using facial recognition). The application of this in the art world is a greater application to recognize images and sounds. For example, with the proper devices and computing capabilities, museums can implement technology such as determining if a piece of artwork is a fake work or not.

3. Computerization of the commonplace – Think of this aspect of computing and devices in terms of a “smart house.” Modern infrastructures (i.e. storage of data on the cloud) enables things as simple as a doorbell to expand their capabilities to become “smart” technology. If smart technology has a place within an industry, it’s important to first identify if the computing and devices infrastructure can support this change.

Data Management

Data Management is critical to business success. Higher level processing and productivity within an organization cannot happen without proper data management, so in many ways, data management is the most critical level of the AI stack. Data management is defined as “… the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively.”The path to proper data management for different organizations can take many forms, but below is an example process for establishing data management:

The key to data management ultimately comes down to one word:

VALUE

Data management has shown to bring organizations increased value by streamlining process and revealing where to focus business strategy. In the art industry, this could mean greater customer analytics within an art museum to see which populations visit most often, and therefore which populations to target with promotions and deals. For example, if detailed data management and analytics reveals that families with kids between the ages of 2 and 12 make up the majority of museum visitors over the summer, the museum could focus its displays and programs during those months on catering to that population.

Beyond the art industry, civic organizations and local governments have already shown how much value proper data management can generate: by creating the infrastructure for open source data management, the public sector “… has sparked innovation, driven efficiency, and fueled economic development.” Imagine the possibilities for the art industry if more art organizations do the same.

Machine Learning and Modeling

Machine Learning (ML) is an over-used and often misunderstood term. ML is defined as “…the systematic study of algorithms and systems that improve their knowledge or performance with experience” (Akoglu). In plain terms, ML and modeling are advanced math applied to data using computers. The most promising applications for ML in the art industry currently are the automation of business processes (see below), but there are also many examples for how ML is being used to GENERATE art. For more information on this, check out this Ted Talk on music and art generation using machine learning:

Decision Support, Planning, & Acting

This portion of the stack refers to systems that have surpassed the functionality of modern machine learning. The decision support layer simply “helps humans make decisions,” while the planning and acting layer “…rely on optimization, safety, the knowledge network, and strategic reasoning” to learn from information they are given. It’s difficult to understand why and how this layer is different from ML and AI (or why it fits in between the two layers in CMU’s AI stack), but this layer teaches us that the level of task automation and computer “learning” exists on a spectrum.

Autonomy / Human AI Interaction

Human AI interaction is defined as “… the completion of a user’s task with the help of AI support.” While AI can often be an intimidating concept and mistrusted by those who are unfamiliar with it, it has many potential applications within the art industry for automating production, identifying and maintaining consumer markets, and other task completion and automation.

Ethics

A discussion of the AI stack would be incomplete without stressing the importance of ethics in AI development decisions. Beginning with the data management layer, the art industry has the potential to store and track large amounts of personal data on its customers (similar to other consumer industries). The art industry is largely trusted by its consumers, so as its capabilities within the stack expand, ethical design is critical. Large companies within the art industry have identified its necessity and have started to build infrastructure around ethical decision making which can provide a guide for other smaller organizations. For example, Spotify created an Ethics Guild to make ethical considerations “more concrete.” They created a simple Google document open for other organizations to use that evaluates the decisions within the AI and technology stack that different groups within an organization are making as shown below:

How to Bring ‘the Stack’ to the Arts

1. Increase data literacy

Data literacy is defined as the collection, examination, analysis, and interpretation of data to inform a decision. Using data to inform decisions is one of the most important first steps an organization must take before considering any higher parts of the stack. Organizations can do this by heavily democratizing data (ensuring all members of the organization have access to it) and increasing ease of use whenever possible.

To be clear, data democratization is not synonymous with data anarchy; not every member of the organization should have access to all the data. For example, the managerial and janitorial staff of a concert hall may not need access to detailed demographic data on the concert hall’s visitors and guests. However, it would be very useful for them to have visitor frequency data (what times of the year or what types of shows bring in the most visitors) so that they can plan accordingly for peak bust times.

2. Use art itself

In 2016, an education study was conducted in Brazil that looked at how to increase data literacy in young children. After testing different methods, the research team found that those students who learn using visual arts activities performed far better in tests than those who learned through traditional educational methods. The take-away? When looking at how to bring data literacy and eventually the stack to arts workplaces, use art! It’s proven that people respond best learning a new concept through creative methods.

One of the researchers, Catherine D’Ignazio, identified tactics that could help to build data literacy[2] that included building learner-centric tools and favoring creativity over purity. Teaching technical concepts doesn’t require intensely ‘academic’ verbiage or techniques.

Data literacy is intimately intertwined with increased use of visualizations to communicate results. To generate change within an organization or inspire people to action, visualizations are often the best way to captivate an audience. Consider the visualizations below:

Although beautiful in its colors and layout, the visualization has a specific purpose: to educate people on ways child mortality has been reduced historically. Visualizations appeal to a wide range of emotions (similar to art), and often provide information to viewers that would be lost in traditional reports. For example, if you are a manager for a music production company, creating visualizations that show declining sales in the form of a descending scale on a piece of sheet music, this could grab the attention of the audience more because it is shown in a familiar medium. The visualization options are vast, and the benefits of incorporating art into data management strategies are endless.

3. Automate when possible

During the pandemic, 42% of art organizations had to decrease the number of people on their staff, but 65% were still delivering some sort of content. The arts industry must adopt some form of technology for administrative tasks and distribution in order to stay afloat in an increasingly digital world.

Business automation tasks include the following:

• Responding to emails – when it comes to customer feedback, develop a system to automatically sort and respond to any correspondence an organization receives
• Data management functionalities – depending on the data collection and storage methods used by an organization, data “pulls” and back-ups can be easily automated using out-of-the-box software systems
• Customer engagement – social media posts, emails, and other promotions can be setup on a time schedule so that employee time is not taken up by maintaining a customer engagement schedule

There is a plethora of task automation tools available on the internet, and it is important to develop time to determining the best fit between software systems and the organization.

Conclusion

“I say, run toward the data. Take your data back and turn it into something meaningful.”

Laurie Frick, From Paint to Pixels

The utility of the AI stack is evident: the organizations that choose to implement it will succeed, while those who fail to implement will likely cease to exist. Although it seems overwhelming to implement the stack within the art industry, organizations can start simply by focusing on the data. Strive towards data literacy and education. It may be the decision that saves the arts.

References:

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Akoglu, Leman. “Lecture 1: Machine Learning: Basic Concepts.” (Spring 2019). Course Notes for 95828: Machine Learning for Problem Solving.

“AI Stack” (2022). Carnegie Mellon University. Retrieved May 3, 2022 from https://ai.cs.cmu.edu/about

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Batti, Khadim (Feb 6, 2020). How Technology Could Impact the Workplace Over the Next Decade. Forbes. Retrieved March 8, 2022 from https://www.forbes.com/sites/forbestechcouncil/2020/02/06/how-technology-could-impact-the-workplace-over-the-next-decade/?sh=620396fb3bd2

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Goldstein, Brett and Lauren Dyson (2013) Beyond Transparency: Open Data and the Future of Civic Innovation. Published by America Press, San Francisco. Retrieved March 8, 2022 from https://beyondtransparency.org/

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The Pineapple Fund

One of the earliest examples of crypto philanthropy is The Pineapple Fund, a 2017 project driven by an anonymous crypto whale (an individual who holds so much cryptocurrency that they have the potential to disrupt its valuation) known as “Pine.” At the end of 2017 and as the value of bitcoin skyrocketed to nearly $20,000/coin, this anonymous donor held an application process for nonprofits to make their case to receive significant cryptocurrency donations. Ultimately, The Pineapple Fund transformed 5,104 Bitcoin into approximately $55 million in support of 60 charitable organizations, most of which were U.S.-based nonprofits. These organizational recipients represented a wide spectrum of crypto fluency. Some organizations worried that Bitcoin was “blackmail money” and were apprehensive about taking the necessary steps to receive their gifts. Other organizations called upon people in their networks who were well-versed in crypto and were able to set up their wallets with ease. The organizations also varied in their ability to translate this one gift into greater crypto-philanthropic momentum. Some invested in learning the crypto infrastructure and capitalized on the PR opportunity to leverage further donations, while others floundered to provide a clear pathway for future donors. 

This is a notable case study because it is an example of a big player in the crypto world tipping nonprofit organizations toward progress. Without Pine’s intervention and generosity, these organizations would have continued in their traditional fundraising activities and may not have ventured into the uncharted crypto waters for many years yet to come. It is also worth noting that, of the 60 charities that received funds from The Pineapple Fund, none appear to be oriented toward arts and culture missions. While the ways that blockchain technology (especially NFTs) is disrupting the art world are well documented, it appears that arts nonprofits may be behind the curve in this philanthropic area.

Crypto Philanthropy: Why Pay Attention?

Crypto philanthropy is not just a fad based on the whims of the mega-wealthy like Pine, but is actually an innovative fundraising pathway that organizations should be working to capitalize on. Julie Couturier for the Dorothy A. Johnson Center for Philanthropy has identified crypto philanthropy as one of the most salient trends or topics for nonprofit organizations to keep an eye on in 2022. According to her research, crypto philanthropy is a growing avenue, citing that “cryptocurrency contributions to donor-advised funds (DAFs) at Fidelity Charitable Trust (2021) more than doubled from $13 million in 2019 to $28 million in 2020,” and that “the value of total cryptocurrency donations is now over $300 million annually — and is only expected to grow.”
This movement toward crypto philanthropy can be significantly attributed to wider adoption of cryptocurrency investments amongst the philanthropically-inclined Millennial generation. 13% of all investors currently participate in the crypto market, but Millennials are disproportionately invested in crypto (35%) or express interest in entering the market, compared to investors overall. Furthermore, Millennials tend to be more generous than the general population; almost 90% identify “charitable giving [as] an important part of their lives.” As nonprofits express desires to diversify their donor pools and attract younger donors, it follows that these organizations should want to explore this opportunity.

How to Accept Crypto Donations

In order to move into the crypto philanthropy space, organizations and their leaders need to make informed decisions about the kind of pathway they want to create for their crypto-donors, how much involvement staff can/should have, and what related, internal policies need to be created. Tina Roh, co-founder and COO of Every.org, identified four methods for accepting cryptocurrency:

1. Use an intermediary 501(c)3 to minimize legal, accounting, and administrative burdens
2. Use a crypto donation processor to receive crypto directly
3. Use an embeddable checkout experience through a crypto exchange
4. Use your own crypto wallets and receive donations without any intermediary

Each of these options is perfectly valid depending on the capacity of the organization and the degree of familiarity and fluency that staff has in this Web3 space. For instance, option #1 looks a lot like (and in many cases, is) donating to a donor-advised fund (DAF). The DAF is, itself, a nonprofit that acts as a middleman. DAFs accept the cryptocurrency donation, immediately cash out to reinvest the money into the overall fund, and then disburse gifts to one or many nonprofit organizations. This process is appealing to nonprofits because it occurs without involving the ultimate beneficiary organizations in any of the technical mechanisms of receiving or converting the crypto gift. Crypto-investors may prefer this method as well because it is tax-efficient and gives donors current and ongoing input on what impact their money has.

Endaoment is one such DAF seeking to be a “new kind of community foundation.” Based on the Ethereum blockchain, Endaoment utilizes digital smart contracts to award grants to various nonprofit organizations. From there, beneficiary organizations may choose to either have their gifts transferred to a bank account as U.S. dollars for a standard $15 fee or to a cryptocurrency wallet for essentially no cost. However, if organizations choose to hold their awards in their crypto wallets, they become subject to the volatility of the markets.

As for option #2, there are now a variety of crypto donation processors on the market that nonprofit organizations may choose from. Platforms like Engiven, The Giving Block, and BitPay are for-profit companies that can act as third-party facilitators of crypto donations. These services cost a nominal fee (usually a percentage of the donation) but save fundraising professionals from having to develop highly specialized, technical skills in addition to everything else that they do. Engiven, for example, recently launched two new services: the automatic creation of necessary tax forms and a free, automatic appraisal for donors giving gifts valued at more than $5,000. These automatic functions save development staff the time and effort of assembling forms and eliminates the appraisal expense which previously would have fallen to donors.

Every.org is a particularly interesting processor option because it is also a 501(c)3 private foundation with a mission “to build accessible giving infrastructure to help every person and organization use technology for good.” Every.org funnels donors through Coinbase, which charges its own 1% fee, but offers its services to nonprofit organizations for no additional cost. Every.org also generates the necessary tax receipts automatically and “handles compliance,” making it a low-touch option for fundraising professionals.

Whereas Every.org facilitates donations by creating a more complete donor experience around an embeddable service like Coinbase, some nonprofits may elect to use products like Coinbase or BitPay directly. In these scenarios, organizations would take on a higher burden around donor processing, data collection, tax acknowledgments, and technological upkeep. The upside, however, is that these institutions would reap the benefit of lower fees compared to other more comprehensive services, making it a particularly viable option for tech-savvy staffs.

Lastly, organizations could opt to simply set up their own crypto wallet and handle donations directly. This is the most burdensome on the development or organizational staff at large because it requires much more technological infrastructure to be developed in-house surrounding the actual transaction. Staff will have to research and choose a cryptocurrency wallet that best suits the needs of the organization and institute careful policies around keeping the wallet and its passphrase secure and how much cryptocurrency they actually want to hold at any point in time. Because “the ability to operate anonymously is a central tenet of crypto technology,” organizations that choose this route will also have to build in processes to collect the necessary data to maintain detailed and useful databases and provide donors with tax documentation. Collecting and organizing crypto-donors information in one’s database will be particularly useful as these donors have specific interests or priorities that development staffs should want to cater to directly.

Conclusion

Crypto-philanthropy is a promising, largely untapped opportunity for nonprofit organizations, especially those in the arts and culture sector. Some institutions are slowly beginning to enter the Web3 space. The Great Lakes Science Center began accepting Bitcoin admission payments in 2018. The Institute of Contemporary Art, San Diego works with The Giving Block to facilitate crypto-philanthropy gifts and even advertises their CryptoClub, a special tier of donor recognition with premium benefits specifically for crypto-philanthropists. 

However, money is being left on the proverbial table. A majority of cryptocurrency investors are not aware that their investments can be donated to charity, leaving a significant portion of these philanthropically-inclined individuals in the dark about the tax benefits of such philanthropy, both in terms of avoiding capital gains tax as well as the tax deductions associated with traditional charitable giving. Then, of investors that want to pursue such donations, 46% report difficulty in finding charities that will accept the donations.

Alongside the need for greater organizational knowledge about how to engage crypto-philanthropists, organizations will also need to develop or deepen internal policies around cryptocurrency and investments. Some of these platforms allow organizations to receive in U.S. dollars donations that began as cryptocurrency. In other cases, the organization is directly trafficking in crypto and needs to write and abide by clear policies regarding how much of a donation can be held in its crypto form and for how long, especially given the extreme volatility of these markets.

Though the crypto-philanthropy field is still maturing, early players like the United Way have been accepting cryptocurrency donations for nearly a decade and the Kennedy Center has identified the founders of The Giving Block among the 50 leaders leading arts and culture into the future. The market has a wide array of platforms available to help facilitate donations from the many interested and motivated donors who represent a younger, dynamic, and innovative segment that development professionals would be excited to reach. It is now up to organizations to step up and seize the opportunities at hand.

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In 2021, TikTok updated its privacy policy which allowed it to collect biometric data on its users, including faceprints and voiceprints. Rather than explicitly informing its users about this change, they only communicated that they were issuing a “privacy update” upon opening the app. Once people found out what the update entailed, they started growing concerned, and rightfully so. It’s a significant shift from companies collecting behavioral data on their consumers to something a little more invasive and without consent. Only 36% of Americans trust tech companies using facial recognition technology. In general, public trust in big tech has been steadily falling in the United States. Yet most of us still click “accept” to the Terms & Conditions on any website without actually knowing what we agree to. There’s been an apparent disconnect between what we expect from US businesses and what we blindly agree to.

What is Data Privacy

Everyone has data – name, age, gender, birthday, interests, browsing habits, etc. These aspects of a person’s identity fall under the Personal Data category. That data is valuable to big corporations, whether they sell the data to gain revenue for free services to their consumers or buy the data to advertise their products to potential consumers in a tactical, albeit intrusive, way. In the notorious  2018 Senate Hearing on Facebook, Mark Zuckerberg’s retort, when posed with the question of how Facebook remains profitable when its service is free, gave us a glimpse into an obvious yet disturbing truth behind the operations of a big tech company. “Senator, we run ads,” followed by a cheeky smirk. The purpose of data in the capitalist sphere we’ve grown all but too familiar with in the US has become predictive modeling of human behavior.

Data privacy can be defined as the careful handling of data throughout its lifecycle, from data creation to data deletion, based on its relative importance. It’s a field that has grown exponentially in the digital age, dealing with the management of data, governance, compliance, laws around it, consents, notices, and regulatory obligations. The Health Insurance Portability and Accountability Act, better known as HIPPA, is a policy in the healthcare sector that protects against institutions misusing patients’ medical and health data. It prevents healthcare organizations from giving out patient information on their physical and mental health and requires that healthcare and healthcare insurance industries protect this information from fraud or theft. This policy prevents insurance companies, pharmaceutical companies, and doctor’s offices from directly targeting people with personalized ads for products or services. HIPPA is the only sector-specific policy in the United States that protects people from having their personal information abused or exploited by large corporations. With only three states having adopted some form of data privacy law, it’s unclear how soon Congress will propose bi-partisan data privacy legislation. For the time being, it’s up to the individual states.

Legislation

It’s no surprise that the United States government is behind on data privacy regulation. As with many contemporary issues, it often takes a while for the government to create bi-partisan cooperation toward implementing change. Currently, the European Union is leading the data privacy venture with the General Data Protection Regulation (GDPR). Its creators intended for it to be the toughest privacy and security law in the world to date. Much like the right to the pursuit of liberty or free speech, the new EU regulation is stalwart in the idea that “the protection of natural persons concerning the processing of personal data is a fundamental right.” Under this regulation, EU citizens have the right to ask companies how their personal data is collected, stored, and used. They also have the right to request that their data be deleted from a company’s database (or CRM). Companies must get consent from a consumer before collecting and storing their data. With the exception of HIPPA, there is no centralized regulation that protects US citizens’ personal information from being abused by companies.

The closest piece of legislation we have exists only in California, whose government passed the California Consumer Privacy Act (CCPA) in 2018. Under CCPA, citizens have similar rights to those established in GDPR, except for a few differences. But it can be inferred by the name that CCPA only applies to California residents. Similar pieces of state legislation were passed in Virginia (the Consumer Data Protection Act) and Colorado (the Colorado Privacy Act), both in 2021. The biggest hurdle appears to be the extent to which Democrats and Republics want big companies to be penalized for mishandling personal consumer data. While Democrats want to enable consumers to hold businesses accountable for abusing their data, Republicans opt for more business-friendly legislation. Without centralized federal regulation, having varying data privacy laws by state makes the issue much more complicated. It leaves consumers unsure or unaware of their rights.

The Artist Experience

In 2016, Mozilla partnered with Tactical Tech to bring the Glass Room to London and New York City. This immersive exhibit, made to look like a tech store, was created to teach people about who is collecting their data online and why. The Glass Room attempts to demystify the world of data privacy in a vast digital world where one can lose themselves without knowing it. It does so by getting participants to think about how they interact with online platforms and helps visualize and contextualize otherwise abstract ideas.  

To move through the Glass Room is to be reminded of the many ways we unwittingly submit ourselves and one another to unnecessary surveillance, with devastating consequences

The New York Times

As with any other complex social issue, artists have been quick to be the messengers of social and moral concern. The beauty of the arts is that they can convince people that they need to care about something. Humans are inherently visual creatures, but it sometimes takes more than just showing an audience why something is a problem. Some artists have gone so far as to make an audience live a problem, either in an immersive exhibition or through some “alternate universe Black Mirror” way. One such experience is German artist Tobias Leingruber’s Facebook ID card project. In 2012, Leingruber created Facebook ID cards for his guests at an art event. This concept was somewhat influenced by George Orwell’s 1984. Leingruber’s project lends commentary to how social media pervades our everyday lives. If we allow digital platforms to consume our identity little by little, where is the line drawn? And because we give such importance to having an online presence, is it really unimaginable that one day we base our value on the digital content we so meticulously curated to achieve some level of social status?

Netflix’s Black Mirror episode Nosedive also played with this idea in 2016, in which a woman’s life unravels over her slowly deteriorating “social media score” as she desperately tries to cling to the small amount of social standing she has. While these are two extreme examples (thankfully, in the ten years since, Leingruber’s fake project hasn’t become a reality), the main question coming to my mind is what happens to us when nothing is private anymore? In the United States, citizens are very well aware of their rights as established by the Constitution. Yet when a significant data breach at a big company occurs, collectively, we aren’t as outraged by it. This isn’t to say that civil and constitutional rights aren’t as necessary. But as the EU established in the GDPR, “the protection of natural persons in relation to the processing of personal data is a fundamental right.” As more of our personal lives become exposed and our habits become exploited by big business, how does the nonprofit sector factor into all this?

Arts Nonprofits’ Adaptability

In a society where technological trends feel almost ephemeral, it’s understandable why many nonprofit art organizations are slow to adopt the most up-to-date data collection, storage, and management technologies. Several factors come into play, like lack of funding, tech-hesitant Boards of Directors, and a general lack of awareness of systems that would make the work more efficient. Even many for-profit entities are behind the curve when it comes to having a data strategy. But as opposed to for-profit businesses, nonprofits could be using data from their communities to create more effective programming tailored to their target audience’s needs. These efforts are crucial to achieving its mission. One author noted that when organizations lack the data architecture to fully leverage the data available to them, the actual opportunity cost is innovation.

Knowing how to use the data is only part of the equation, though.

As if investing in data collection and management alone wasn’t a whole new world for nonprofits, we now add the complex issue of consumer privacy into the mix. The lack of US regulation around data privacy begs the question: what responsibility do the private and nonprofit sectors have in this realm? While there is little US legislation for the private sector, there is even less for the nonprofit sector, leaving organizations even more in the dark. Yet, data has become more crucial than ever in understanding their target demographic, creating appropriate programming, and effective marketing materials in nonprofits. However, the lack of data architecture and policies leaves nonprofit organizations vulnerable to data breaches equally, if not more. The New Jersey Shakespeare Theater experienced a ransomware attack in 2019. Hackers disabled the organization’s access to its ticketing system and patron database. Several other breaches have occurred in which hackers gained access to an organization’s funder information, costing them tens of thousands of dollars, practically forcing some to shut down.

Because nonprofits don’t operate as a traditional “business” and because those kinds of data breaches don’t typically make headlines, this may be seen as a trivial issue. But as entities that hold personal identifying information on patrons, donors, employees, and Board members, nonprofits have just as much an obligation to protect their data as do for-profit businesses. The following are starting points nonprofits should heavily consider in developing a long-term strategy for data storage and protection:

• Understand the legislation (discussed above) that exists to develop protection plans
• Form a data and cyber security governance committee
• Embrace cloud-based storage software
• Properly educate employees on data security

Conclusion

The arts can be used to inform the public about this issue and make it understandable through a more tangible medium. With the current lack of legislation in the United States, the arts can bring awareness to this issue and empower the public to push the federal government to implement change. All in all, nonprofit arts organizations have the same responsibility as for-profit and government entities to protect personal consumer data and use it ethically. The relationship between people, their data, and business is significantly unbalanced. But artists and arts organizations can help restore the balance by acting in the best interests of the public and using legislation such as the GDPR as a reference.

Resources

Alexander, Alistair. “The Glass Room: Big data, privacy and interactive art.” Mob Lab. April 28, 2018. https://mobilisationlab.org/stories/big-data-privacy-interactive-art/.

Crittenden, Elizabeth. “Let’s Talk: TikTok’s Privacy Update And Incubator For Black Creatives, Spotify’s Speech Recognition Technology, And More.” Arts Management & Technology Laboratory. June 22, 2021. https://amt-lab.org/podcasts-interviews/2021/6/lets-talk-tiktok-privacy-update-and-incubator-for-black-creatives-spotify-speech-recognition-technology.

DalleMule, Leandro and Thomas H. Davenport. “What’s Your Data Strategy?” Harvard Business Review. May-June 2017. https://hbr.org/2017/05/whats-your-data-strategy.

“Data Privacy – Definitions, Importance, Legislations / Privacy laws.” Data Privacy Acts. May 12, 2020. https://dataprivacyacts.com/data-privacy-everything-you-need-to-know/.

Fang, Jiashun. “What Makes Facial Recognition Controversial?” Arts Management & Technology Laboratory. February 13, 2020. https://amt-lab.org/blog/2020/2/what-makes-facial-recognition-controversial.

Frankfurt, Tal. “How To Avoid Security Breaches In The Nonprofit Sector.” Forbes. March 31, 2021. https://www.forbes.com/sites/forbestechcouncil/2021/03/31/how-to-avoid-security-breaches-in-the-nonprofit-sector/?sh=1be2a0095ce0.

Fried, Ina and Mike Allen. “Exclusive: Trust in tech craters.” Axios. March 31, 2021. https://www.axios.com/edelman-trust-barometer-tech-5787acea-8ef5-4d0b 96946e4f8eb006c4.html.

GDPR.eu. “General Data Protection Regulation (GDPR).” Accessed April 6, 2022.  https://gdpr.eu/tag/gdpr/.

Jehl, Laura and Alan Friel. “CCPA and GDPR Comparison Chart.” Baker Hostetler LLP.  Accessed April 30, 2022.     https://www.bakerlaw.com/webfiles/Privacy/2018/Articles/CCPA-GDPR-Chart.pdf.

“Legislative Preview: Data privacy”. Congressional Quarterly Magazine. February 14, 2022. https://advance-lexis-com.cmu.idm.oclc.org/api/permalink/73df9d80-2c49-4f29  a233-3ca744502911/?context=1516831.

Leingruber, Tobias. “FB Bureau Berlin: Get Your Fb Identity Card!!” Free Art and Technology Lab. February 24, 2012. http://fffff.at/fb-bureau-berlin-get-your-fb-identity-card/.

NBC News. “Senator Asks How Facebook Remains Free, Mark Zuckerberg Smirks: ‘We Run Ads’ | NBC News.” April 10, 2018, 1:00. YouTube video. https://www.youtube.com/watch?v=n2H8wx1aBiQ.

“Nosedive.” IMDb. Accessed April 30, 2022. https://www.imdb.com/title/tt5497778/.

Pardes, Arielle. “What Is GDPR and Why Should You Care?” Wired. May 24, 2018. https://www.wired.com/story/how-gdpr-affects-you/.

Pyne, Lydia. “A Data Artist’s Guide to Putting People (and Privacy) First.” Hyperallergic. May 6, 2021. https://hyperallergic.com/641187/living-in-data-jer-thorp/.

Rippy, Sarah. “Colorado Privacy Act becomes law.” IAPP. July 8, 2021. https://iapp.org/news/a/colorado-privacy-act-becomes-law/#:~:text=Sarah%20Rippy%20IAPP%20Member%20Contributor%20On%20July%208%2C,earlier%20this%20year%2C%20to%20enact%20comprehensive%20privacy%20legislation.

Rippy, Sarah. “Virginia passes the Consumer Data Protection Act.” IAPP. March 31, 2021. https://iapp.org/news/a/virginia-passes-the-consumer-data-protection-act/.

Schenker, Dylan. “Artist Explores Online Identity and Privacy With Facebook ID Cards.” VICE. March 5, 2012. https://www.vice.com/en/article/z4y5z8/artist-explores-online-identity-and-privacy-with-facebook-id-cards.

State Of California Department of Justice Office of the Attorney General. “California Consumer Privacy Act (CCPA).” Accessed April 22, 2022. https://www.oag.ca.gov/privacy/ccpa?msclkid=7dc2492cbd9411ec867bf5984af6282d.

“The Week in Breach: 12/04/19 – 12/10/19.” DeckerWright Corporation Blog. December 11, 2019. https://www.deckerwright.com/blog/the-week-in-breach-1-5.

“What is CRM?” Keap. Accessed May 2, 2022. https://keap.com/product/what-is-crm.

Younanzadeh, Emanuel. “Why Your Company’s Data Architecture Is More Important Than the Data Itself.” Forbes. April 13, 2022. https://www.forbes.com/sites/forbescommunicationscouncil/2022/04/13/why-your-companys-data-architecture-is-more-important-than-the-data-itself/?sh=609e81e85311.

Blockchain, while a relatively new concept, is becoming more common to hear about in the media and news. You may have heard recently Snoop Dogg revealed himself as the Twitter-famous NFT influencer, Cozomo de’ Medici or Tesla started accepting Dogecoin payments for some of their merchandise, but most people are still wary of this technology and how is it applicable to Broadway? “Broadway” is considered the home of the American theater industry and is located between 42nd and 53rd street, including Times Square, in New York City. The Broadway industry contributes $14.7 billion to the economy of New York City, on top of ticket sales, and supports 96,900 local jobs. In the 2018-2019 Broadway Season, attendance reached 14.77 million people, with many people seeing more than one show. Broadway greatly vitalizes the economy of New York City and the millions of audience members who visit a show annually, so how is this artistic giant entering the technological space of blockchain, cryptocurrency, and NFTs? With the pandemic shutting down Broadway, very few theaters with plans to explore this technology were able to proceed, yet as Broadway reopens, we are mostly seeing Broadway utilizing blockchain for ticketing services.

What is Blockchain?

Before going into detail about how this technology is being invested in by the Broadway industry, lets define blockchain and why it is so popular. Blockchain is a public ledger of digital information, i.e., it is a secure network on top of the internet. Information in blocks can be anything; a transaction, contract, ownership, identity, money, agreement, or anything that has some value. As each transaction occurs, information gets recorded as a “block” of data, with each block being connected to the block before and after it. Transactions are linked together in an irreversible chain, aka blockchain. Some characteristics of blockchain include:

• “It is immutable – it cannot be modified but one can append the block in the chain
• Data is encrypted and stored in a decentralized manner
• No redundant data
• No central authority
• Anyone in the network can see it using public/private keys
• No transaction cost
• Recorded with timestamp”

Many industries are turning towards blockchain due to the greater trust people have in the technology, the greater security it offers its users, and the efficiencies it offers businesses.

Broadway and Blockchain

The largest Broadway theater landlord, The Shubert Organization, announced its pilot program to utilize blockchain technology “to sell Broadway tickets on their website, telecharge.com”, in 2019. There are many reasons why the Shubert Organization might want to implement blockchain technology, yet two stand out and they both lead to greater profit for the giant theater owner. According to Lee Rodriguez, author of “Shubert Organization set… thwart secondary ticket brokers,” these two reasons include:

“First, is that it may help to eliminate secondary ticket brokers. For a ticket to be used electronically, the blockchain would have to be updated due to the security measures inherently within this technology. This data would ultimately give The Shubert Organization exclusive data about the true value of Broadway tickets and how many are resold after they initially sold the ticket. This data would then allow Shubert to adjust their own prices to reflect true market value by cutting out the ticket brokers profit, essentially bankrupting them. The second way The Shubert Organization could monetize the use of blockchain is through the data they would store and collect on the blockchain from their audiences. They could use the data to market directly to those customers or similar customers again, cutting out the middleman marketing agency.”

Data that Lee Rodriguez states can be stored includes:

• “Original ticket price, show, location, date, and time
• Who bought the tickets and at what price
• Subsequent ticket sale prices and buyer’s details
• Previous transactions, including buyer information and sale price
• Whether or not the buyer actually attended the show or was a no-show
• Fingerprints and/or picture of the ticket owner (and past owners) to identify theatregoers at the theatre entrance via facial recognition
• Data about the current owner, including age, race, height, sex, and Broadway ticket purchase history”

By using blockchain for ticketing, this eliminates the threat of being scammed by fake tickets. While concert tickets have about 12% fake tickets circulating at any given time, research has shown this is not as much of a threat for Broadway tickets. However, organizations can market their use of blockchain as an extra security measure for audiences. While COVID slowed down the trial of this technology for Shubert, there are some other considerations they may need to review before completely implementing blockchain. Lee Rodriguez continues his article to list considerations, such as:

• “Following an internal review, the other primary Broadway ticket vendor, Ticketmaster, is not planning to use blockchain technology. However, Ticketmaster is looking into it for NFL tickets, where the number of fake tickets is extremely high
• Ticket buyers may not want their data stored in the blockchain and have privacy concerns
• Secondary ticket brokers will have a tough time buying into this technology, if it is used to hurt or close their business
• Eliminating ticket brokers would actually raise the original price of Broadway tickets
• The secondary ticket market brokers often drive Broadway ticket sales. Without them a good piece of the total marketing effort is gone. This may ultimately lead to loss of demand for Broadway tickets”

Another Broadway theater, Roundabout Theatre Company, successfully launched the use of 22,000 blockchain-enabled, secure, contactless digital tickets this year by being the first Broadway client of a service called True Tickets. True Tickets is a “secure contactless digital ticketing service that can be tailored to a venue’s specific needs.”

“The data tells the story. Our audiences have overwhelmingly adapted to the experience of digital tickets. True Tickets allowed us to streamline our operations while promising to provide significantly more insights into who is attending our performances. True Tickets has been a seamless addition to the customer experience and has enabled us to take a big leap toward making ticketing a more strategic function. Moving forward, we can better understand and engage our audiences, explore the benefits and potential applications with additional distribution channels, and ultimately create an even better experience for patrons.”

Gabe Johnson, Director of Sales and Analytics at Roundabout

True Tickets also partners with the “Adrienne Arsht Center in Miami and the Dr. Phillips Center in Orlando”. True Tickets is able to seamlessly adapt into Tessitura, the ticketing software system used by many nonprofits, to ensure a consistent, positive experience for patrons. The Shubert Organization and Roundabout Theatre Company have varying degrees of success and positive reception to implementing blockchain into their ticketing services, however I do believe more theaters will shift as success becomes apparent and the technology becomes less elusive.

Blockchain and Other Ticketing Events

While we have learned that fake tickets do not seem to be roaming the Broadway circuit much, there is much higher likelihood of encountering them when purchasing a highly sought-after concert ticket or sporting event. The music industry and sporting industry have already experimented and implemented blockchain ticketing on a much higher level than the theater industry. The advantages these industries gain is no different than to the Broadway industry, Broadway is just known to be slower at adapting to technology. There are specific events that tend to have a higher need and greater success in implementing blockchain-enabled tickets, such as:

• The event is in high demand
• The event has a strong potential for ticket resale
• You want to control who can to re-sell tickets
• There is an active community of fans around your event

Another interesting aspect that ticket sellers can control with blockchain-enable ticketing is attaching a “smart contract” to your ticket. This would, in theory, allow an artist to set a price for an event and scalpers would not be able to change it by price gorging. How many times have you wanted to see your favorite artist in concert but it sold-out in minutes and the only available tickets are from third-party sellers with a 300% profit margin? Smart contracts would completely eliminate this issue for fans, as well as the potential of purchasing a fraudulent ticket. Ticketmaster is currently trialing this technology internationally; a successful run could completely change how ticketing systems work. “Ticketmaster is used by some of the world’s most renowned artists and high-profile events in the entertainment industry.” Many Broadway shows utilize Ticketmaster to sell their tickets, so if Ticketmaster decides to widely implement this technology, many theaters will have no choice but to follow suit.

Blockchain, and Cryptocurrency, and NFTs, Oh, My!

We already are seeing how this technology is taking shape with selling Broadway tickets, however there are some other forms of blockchain that may make their way to The Great White Way in the near future. Very few people are experimenting with these technologies currently, but there are some interesting uses. The producers behind Slave Play and Ratatouille: The TikTok Musical, Seaview, are bringing non-fungible tokens (NFTs) to Broadway. Seaview describes NFTs as, “Digital assets, including photos, videos, GIFs, tweets or digital designs, which are then sold and resold on the blockchain using cryptocurrency.” Seaview, in partnership with a few other companies, have created an online platform to sell Broadway memorabilia as NFTs. Now, fans can purchase their Broadway gifts and souvenirs in the form of NFTs, along with their typical t-shirt or tote bag. The Wrong Man, a new Broadway musical slated to open in 2023, will open its own NFT webstore that features collector’s items surrounding the musical. While physical souvenir stands in Broadway theaters are not going anywhere anytime soon, there may be more emerging NFT webstores for specific shows working in tandem with tangible merchandise. What these companies hope to accomplish by creating Broadway NFT marketplaces is “to develop an industry presence in the emerging technology space and to potentially provide another revenue stream for Broadway businesses“. Another interesting future includes the use of cryptocurrency to invest in Broadway-bound productions. Producers have to follow pretty strict laws to find accredited investors when looking for financial backing for a new production. This is to ensure security for both parties involved. While these laws are not established for accredited investors using cryptocurrency “assets”, this realm may need to establish guidelines as we may one day see cryptocurrency being used as funding by Broadway producers.

Conclusion

Blockchain technology is infiltrating many industries due to its many advantages, such as greater trust, greater security, improving operations, improving efficiencies, and greater opportunity for profit within businesses. While Broadway is on the slower side to adapt to innovative technology, the implementation of blockchain within their ticketing systems is prevalent and expanding. This tool allows greater control for theaters and producers to track their tickets, as well as gather data on their audiences. Blockchain-enable tickets completely removes the chance of purchasing a fake ticket, as well as attempts to control third-party price gauging. While there are many advantages to this technology, theaters should still consider how their audiences will respond in regard to their data privacy and if a greater control on pricing will negatively affect the Broadway economy. Blockchain has made its Broadway debut and will not be leaving anytime soon, so it is important to work out any challenges while it is still being integrated into common ticketing systems.

Bibliography

Blockparty. “Blockparty 2018: The Year in Review.” Medium. Medium, January 3, 2019. https://medium.com/@goblockparty/blockparty-2018-the-year-in-review-edc2fbdc9b78.

CoinMarketCap.” CoinMarketCap Alexandria. CoinMarketCap, December 24, 2021. https://coinmarketcap.com/alexandria/article/top-10-craziest-crypto-stories-of-2021.

Hernandez, Ornella. “True Tickets Powers Blockchain-Based Broadway Tickets Sales.” Cointelegraph. Cointelegraph, March 2, 2022. https://cointelegraph.com/news/true-tickets-powers-blockchain-based-broadway-tickets-sales.

Huston, Caitlin. “NFTs Come to Broadway in New Venture By Seaview, Marathon Digital.” Broadway News, July 15, 2021. https://broadwaynews.com/2021/07/15/nfts-come-to-broadway-in-new-venture-by-seaview-marathon-digital/.

Insights, Ledger. “Ticketmaster Owner Live Nation Partners with Blockchain Ticketing Firm.” Ledger Insights – enterprise blockchain, April 13, 2021. https://www.ledgerinsights.com/ticketmaster-owner-live-nation-partners-with-blockchain-ticketing-firm/.

“Invest in Broadway with Cryptocurrency Bitcoin.” InvestingBroadway. Accessed April 18, 2022. https://www.investingbroadway.com/invest-cryptocurrency-in-broadway#:~:text=Can%20I%20Use%20Bitcoin%20To,invest%20in%20a%20Broadway%20show.

“NYC DATA: Culture.” NYCdata | Culture. Accessed May 3, 2022. https://www.baruch.cuny.edu/nycdata/culture/broadway-economics.htm#:~:text=Broadway%20contributes%20%2414.7%20billion%20to,the%20season%20grossed%20%241.83%20billion.

Paul, Andrew. “NFTs Aced Their Audition and Are Coming to Broadway.” Input. Input, January xxxxl13, 2022. https://www.inputmag.com/culture/nfts-aced-their-audition-are-coming-to-xxxxlbroadway.

Qureshi, Mehab. “Here’s How Blockchain and NFT Ticketing Can Cut out Middlemen and Resellers.” The Indian Express, October 29, 2021. https://indianexpress.com/article/technology/tech-news-technology/heres-how-blockchain-and-nft-ticketing-may-change-the-ticketing-industry-for-good-7595704/.

Rodriguez, Lee. “Shubert Organization Considers Blockchain to Thwart Ticket Brokers.” NYTIX. Accessed April 4, 2022. https://www.nytix.com/news/shubert-organization-blockchain.

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Studio Team, EventMB. “Blockchain and NFT Ticketing: The 2021 Guide.” EventMB. EventMB, August 10, 2021. https://www.eventmanagerblog.com/blockchain-ticketing.

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Introduction: 

DAO!, it stands for Decentralized Autonomous Organization, a term you might hear out of the pages of anarchist science fiction novel. A group of individuals convene over the internet, discuss a communal goal over a Discord server, then pool their funds for collective action of unprecedented scale. DAO’s have been used to acquire rare artifacts, manage investment funds, and produce collective art.  The arbiter of this collective? A software managed on the blockchain. Enter the DAO. 

The story of DAOs begins in 2016 with a whitepaper aptly named, The DAO. In the whitepaper the writers describe a system of governance maintained by a series of smart contracts to manage an underlying pool of crypto assets that exist on blockchains, such as Bitcoin, WBTC, and Ethereum. Members could trade in their cryptoassets, adding them to a treasury in exchange for native tokens. These tokens were equivalent in value to a portion of The DAO’s treasury and could be cashed out in a process called “burning”. Decision making was delegated to a sub-group of leagues whose members could make a proposal that included deliverables, permissions, a timeline, and outcomes for a mandated action on the DAO. Once a mandate was approved by a majority vote, the smart contract would process the action and the coded instructions would be deployed.

This process worked exceptionally well for cryptocurrency investment whose underlying structure was built on the same blockchain codes used in the smart contracts. In it’s first year, the DAO raised $150 million in assets from 11,000 participants. However, the system was far from perfect. Later that year, an unknown bandit exploited a vulnerability in the DAO’s redemption model, redeeming about 1/3 of the investment pool’s capital. Ultimately, the DAO shutdown, and the managers of the Ethereum Blockchain create a hard fork in the protocol that created two blockchains and restored the original funds to the DAO’s investors. Despite the early failures and risks realized, this experiment in asset management built the foundation of Web 3.0’s participation in collective governance.  Further DAOs such as the Maker Protocol iterated on the DAO’s model to create a cryptocurrency called DAI, one of the first “stablecoins” that automatically buys and sells assets to create a treasury where one DAI is valued at approximately 1$. 

The New Tao: DAOs’ Domain Expands to Real-World Decisions

The early DAO systems were designed to excel in Web 3.0 decision making where the entire system existed on a blockchain managed through code. However, shortly after this technology’s introduction, DAOs expanded to the management of real world assets. The Constitution DAO was developed in 2021 and raised $47 million over social media networks to place a bid on an original copy of the Constitution. Constitution DAO failed, but the effort set a new precedent.  That year, the PleasrDAO raised $4 million to purchase the Wu Tang Clan’s one-of-a-kind album Once Upon A Time in Shaolin.

The expansion of DAO’s applications continues to grow. DAOs like aGENDA DAO, Herstory DAO, and Friends with Benefits offer members of the public the chance to buy-into membership clubs and vote on projects. Protean DAO was developed to be a platform for crypto-art scholarship and NFT media art conservation with museum level standards. Plantoid and Terra0 Forest go even one step further to create automated systems that “own” themselves and self-perpetuate. Because DAO technology is more of a method than actually a product, the applications of DAOs extend just about any kind of organization that relies on collective governance. Anshika Balla, in her essay, A brief study of Decentrailized Autonomous Organization (DAO) in Blockchain suggests that DAOs can be used for charitable organizations as a method to approve memberships and decide spending, freelancer businesses where contractors combine funds for collective space, materials rentals, and other forms of capital acquisition, and pool investment as a venture fund with redistributions of assets, to name just of few of a DAO’s applications. 

How to DAO: 

Now that we’ve learned the essential elements of DAOs and their applications. You may be asking, how to DAO? There are two ways to get involved with DAOs. Join one or make one! In this next section, we will walk through both processes. 

1. How to Join a DAO

Joining a DAO is easy depends on the DAO you would like to join. Some DAOs are closed from the public, while others have membership tokens that are traded on open markets. Before you join any DAO, you will need to prepare the following: 

1. A Discord Profile ID– Discord is a massive online discussion board platform that hosts live-streaming and text-based conversation channels. This is the popular location of most DAO forums. 
2. A CryptoWallet– This is your address on the Blockchain and the location where cryptoassets are designated and stored. We recommend making a wallet with MetaMask as this appears to be the most commonly used one across platforms, but different DAO platforms may work on different blockchains , so you will first need to double check which wallets are compatible with your DAO of choice. 
3. At least $100 worth of ETH uploaded to your wallet- ETH is one of the fundamental currencies used for Web 3.0 transactions. You will likely need to exchange this currency to either purchase membership tokens for the DAO or exchange it for a currency that you can deposit into it. You can join a DAO without depositing funds, but buying in is the most common way to participate and acquire shares/voting rights.

Now that you have set up your basic infrastructure, you are ready to begin searching for the DAO you would like to join. While it is not the only platform for joining a DAO, we recommend starting on DAOHaus, an app that hosts over 700 different DAOs whose purposes range from accelerating venture products, to Decentralized Financial Management, to building smart contracts, to service guilds, managing arts projects and more. 

Once you’ve scanned around and looked at some of the DAOs to see what members are doing, it’s time to define your purpose. What kind of DAO would you like to join? As this article pertains to Arts Managers, we can narrow our search using the filter tabs on DAOHaus to hone in on clubs, guilds and nonprofit projects. 

Once you’ve found a DAO that you would like to join, you should first join the Discord Server or forum where the conversations of the DAOs are managed. Introduce yourself to the group (you can use a pseudonym) and tell them how you would like to get involved in the project. Most small project DAOs, while operating on decentralized governance, don’t just blindly accept new members, so you will need to first join the conversations before shares can be issued. 

Now that you have joined the forums and began participating in the group discussions, you are half-way there. The next step of joining the DAO is to make a proposal for membership. This proposal will first need to be discussed on the forum and receive informal approval. Once you’ve achieved this informal approval, you can create a proposal on the DAOHaus app. On the proposals page of you DAO of interest, click +NewProposal, request a certain number of shares and offer some cryptoassets as a tribute. When the proposal is submitted, the members of the DAO will be asked to take a vote. If your vote achieves the minimum number of Yes’s then the vote is passed. Yay! You are officially a member of the DAO. Note: You may not be able to directly make a +NewProposal for all DAOs if the DAO is private. In this case, a current member will create a proposal for your membership to issue you shares.

How to Make a DAO: 

Perhaps you are not interested in joining an existing DAO. Perhaps you are already a member of an arts collective, and you are searching for a new management tool that empowers your members to make collective decisions. Well, you’re in luck. A DAO is a perfect solution. For this walkthrough, we are going to assume that you’ve done your homework. You have talked with the members of your arts organization and have decided which elements of it you would like to operate under the DAO model. DAOs do not have to be used for governing the entirety of an organization, but there may be elements that you want to decentralize and democratize. For example, do members of the organization need to access capital for the financing of a small program? Does it have to be micromanaged up a chain of command or can this be operated by those who are taking the initiative? Or perhaps you are a publishing collective having trouble deciding which new product to seed capital investment into or which conventions and conferences to attend for marketing. Why not let the members/volunteers/and customers of your organization decide? By decentralizing certain decision making processes and streamlining the financial resource delegation process under a DAO, your arts organization can free up significant mental space at upper levels of management and expand capacity for more complex projects. Now that you’ve determined the purpose of the DAO you are making, asked constituents the right questions, and built buy-in for your DAO initiative, you are ready to make a DAO. We will use the infrastructure of DAOHaus to complete our process. 

Step 1: Create a Discord-Server/Slack Server or other Communications Management Forum. This will be the home of the communications for your DAO. We recommend using Discord as it’s very easy to scale upwards or keep small and contains many fun management tools within such as polls and video-streaming.

Step 2: Go to DAOHaus and Summon a DAO. At this stage you will want to determine some key information. How many proposals do you want to authorize per day? This will depend on the nature of your DAO’s purpose. How long is a voting period? 1 day? 1 week? What is the grace-period (time between vote approvals and transaction processing) What minimum amounts are deposited and rewarded for proposal seekers? How many wallets/tokens will your DAO manage? DAOHaus has a really good walk-through at this link. (https://daohaus.club/docs/users/summon/)

Step 3: Determine the members of your initial DAO and the number of shares conferred. You will need to have their wallet addresses on file to include them in the initial DAO summoning. 

Step 4: Pay the Summoning Fees

If you are Summoning your DAO on the Ethereum Mainnet Blockchain, it will cost you about 72$ that can be paid in WETH to process the transaction that adds your DAO to the blockchain. Keep in mind that transactions on the Ethereum blockchain have a gas fee. For this reason, you may want to explore other blockchains such as Gnosis or Polygon to host your DAO.

Step 5: Use Your DAO

Congratulations! Once you paid the summoning fees, you are ready to use your DAO. Members and outsiders alike can make proposals according to the rules your DAO has set up, transferring shares and funds from the DAO’s treasury to members wallets. Manage Away! 

Conclusions: DAO’s Potentials and Limits

DAOs present arts organizations with an excellent collective management tool that further increases users participation in Web 3.0 projects. This secondary benefit of including members in Web 3.0 and building fluency within the space empowers members to understand, participate and therefore access capital managed by the users of this space. The global market cap of cryptocurrency is just under $2 trillion, which equates to almost 2% of the world economy. Taken at first glance, 2% may seem insignificant, but when you consider that only 10% of the world population uses cryptocurrency, we can infer that Web 3.0 is still both in its infancy and accesses a significant amount of capital that can be available to those familiar with navigating its waters. 

Lastly, one must consider the risks involved with operating a DAO. It is not a magic panacea that will “run” your organization. As a decentralized process, it requires that at least a quorum of members participate. If you contribute to a treasury but do not vote on decisions made by a DAO, you are essentially handing money over to a group and can lose your voice as a DAO grows in membership. When you exit a DAO, you still must pay a “burn” fee to return your contribution. If a DAO has mismanaged its funds, you stand to lose significantly when you exit and pay the associated exit costs. In this instance, if you did not participate in the decision-making processes of the DAO, then you essentially threw your money away to a group of people who did not represent your interests. A second risk is that a DAO can be gamed. If a DAO lets in members whose intentions are nefarious, they can request a proposal, convince members to approve it, and then walk away with money or shares (voting rights) of the DAO. Therefore it always a good rule of thumb to verify the validity of a member’s claim to work prior to voting yes on a proposal. This dynamic gets murkier when members join a DAO with pseudonyms, don’t actually take the time to get to know each other, and yet scale their DAOs to include more members. 

Finally, the largest risk of participating in a DAO revolves around its legal gray area. DAOs are management tools that represent larger organizations, but not always legally registered ones. Very often the liabilities that members of a DAO are not limited, and debts serviced are passable to the investors in the DAO. In short. Your investment is not protected, so it is best to only participate in DAOs that you wholly trust because you have verified the intentions of its community members. 

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