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.

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The most expensive NFT until now is Everydays: The First 5000 Days by Beeple, originally named Mike Winkelmann, which is a collage of the past digital artworks he created every day. It was the first completely digital art that was bided by a major auction house and finally sold for $69 million in 2021. This sale made him the third most-valued artist after David Hockney and Jeff Koons, regarding auction prices. 

Although first appeared around 2014, the growth of the market for NFTs has been extremely rapid in recent years. In 2021, the whole NFT market was worth $41 billion in total, which is almost close to the total value of the entire global fine art market.

Therefore, as the NFT market booming and generating sales, many more artists are trying to take a step into it. But does every artist really need to be a part of the NFT world and does it really looks like the sweet sugar coat we see from the outside?

What makes an NFT art expensive?

Before we step into the situation and make the decisions, we should first understand the reason behind the phenomenon of NFTs’ prosperities. An article published on Beincrypto by Lulia Vasile pointed out 5 different aspects that make an NFT expensive:

• The reputation of the artist
• The community behind the NFT
• The status symbol that the NFT brings along
• Pop culture
• Technology used

The reputation of the artist:

It’s understandable for people to pursue art from famous artists as it was always like this in the history of the art market for collection and investment purposes. The reason Beeple’s work was selected by Christie’s and sold at this high value is also that he was already well-known with around 2.5 million followers in total on different social media platforms. It’s a lot easier for those artists who are already famous in the field, whether traditional artists or digital artists, to get attention on top of all other works in the sea among collectors if they want to sell their works as NFTs.

A few months ago, Takashi Murakami, the famous Japanese contemporary artist whose physical artworks have been sold worldwide for millions of dollars, announced that he will release a series of 108 NFT works on OpenSea based on his signature sunflower icon. There are already a total of 22.9K ETH amount of trade value within a month of the release. Some people even used bots to reserve the public slots because the artworks are so desirable in the market.

The community behind the NFT:

The NFT communities are often built around owners of NFTs from a specific collection. The more the number of people in the community, the more popular the NFT collection is. Cryptopunks, which are 10,000 unique collectible digital pop-art characters generated randomly by algorithm, is an example of becoming widely-spread thanks to its community members.

The status symbol that the NFT brings along:

As more celebrities come to the NFTs market, some NFTs are becoming symbols of status and popular trends. Thus, out of the mindset of chasing trends, more people would tend to buy those NFTs that have been purchased by celebrities, which makes those NFTs more similar to luxury goods from a psychological perspective.

Pop culture:

The fact that NFTs are embracing Pop art and becoming a kind of pop culture is inevitable. Sharing the common characteristics of Pop art including recognizable imagery, vibrant colors, innovative, and straight-forward, those NFTs that have iconic images and special characteristics are widely known by the public and thus the prices float to a higher level.

Technologies used:

Most NFTs rely on Ethereum blockchains for creations, data storage, and transactions. According to AZ Bigmedia, the components of NFT token metadata can include the artist or creator of the item, the description of the item, the price, the NFT creation date, the ownership of the item, specifications such as royalties, the transaction history of the asset, the new owner, and the location links of the file. There is also a “gas fee” for each transaction because Ethereum transactions need computational energy to perform. The gas fee varies for each sale based on the size of the digital work and the difficulty level of making the transaction. The estimated costs of NFT transactions based on average gas prices are listed below by NFT’s Street:

• Minting cost:  $40-$100 ($70 average) to produce a single ERC721 NFT
• Listing cost:   $10-$20 ($15 average)
• Auction cost: $40-$100 ($70 average)
• Destroying an NFT: $4-$10 ($7 average)

Advantages for artists to embrace NFTs

Admittedly, there are lots of advantages for artists to enter the NFT market and here are some of the most impactful ones.

• Branding: NFTs allow artists to preserve the digital footprints of their works and develop online images of themselves, which can be a good way for artists to enhance their names’ publicity and engage more audiences on the internet, especially on social media platforms.
• Traceability: It’s easier for artists to see where their artworks go and trace the art’s circulations by themselves in regards to NFTs. An NFT certificate has a unique blockchain-based identifier, which allows all the past transaction records about it to be retrieved directly from the ledger of the relevant tokenized asset.
• Resale value and sell-on fees: Based on the transparency and traceability of NFTs, artists can easily get a timely estimate of how much their works are worth in the market. Moreover, artists are supposed to get sell-on fees each time their arts are sold.
• Reach more audiences: NFTs give artists an opportunity to reach broader audiences around the world compared to physical artworks. It’s easier for their works to be seen by collectors and then sold online. Just like a black artist Niall Ashley said, “For marginalized groups, this can help further representation on a global scale.” In the video below, a Nigerian artist Abdulrahman Yusuf creating NFT artworks talked about how NFTs have changed both the art market in Africa and his life. An annual international art fair in Africa also collaborated with the digital marketplace to sell NFTs, which helped open the artists’ options and generate more opportunities to sell their works.

Bursting the dreamy bubbles surrounding NFTs

Although many have been saying that NFTs are empowering artists, especially those independent or emerging artists, to have more choices and make more money from the sales, some other statistics about the market might tell you a different story.

Often seeing the average sale prices on NFT transaction platforms and data collection websites such as Nonfungible.com, artist Kimberly Parker was skeptical about the extremely high value, and did an in-depth research on the medium price of NFT sales to find out if the averages are actually skewed and used to mistakenly represent the whole industry.

According to OpenSea, in 2021, the “average” price of an NFT sold on SuperRare is $5,800; the “average” price on MakersPlace is $2,400; and the “average” on Foundation is $3,500. However, these numbers might be skewed by large sales from those famous artists. Therefore, using the median number might be a more appropriate reference for artists who want to try NFTs.

From the graph above, we can see that most primary sales (the first sale of an NFT) prices fall into the range of $0 to $100, and more than 50% of all recorded sales were under $200. Thus, making money through NFTs is not that easy for most artists.

Another controversial issue surrounding NFTs is the artists’ rights and authorities.

NFTs were supposed to be invented to protect artists’ original works and give artists more control over their works, but it seems to go in the opposite direction. Most NFT platforms are using the same shortcut, so what people have bought is actually a link to the digital artwork, and it’s hard to tell if it’s still the original artwork many years later because the actual digital artwork couldn’t be storaged in a blockchain. According to Anil Dash, the CEO of Glitch, due to technical limits, records in most blockchains are too small to hold an entire image. Moreover, people are creating NFTs based on other artists’ works without their permission, which also hurts those artists’ rights.

In addition, there are still problems with data securities of NFT technologies and the Certificates of Authority in the digital world.

On April 4, 2021, a hacker hacked Beeple’s crypto wallet and minted a fake copy of his most expensive piece Everydays: The First 5,000 Days, the same one sold by Christie’s, on two different NFT marketplaces. Some NFT investors have also experienced the situation where their purchases simply disappeared, and there was no solution to recover the initial investment or the digital asset. Therefore, Daniel Cheung recommends having physical documentation for NFT sales until the technology is mature enough to protect the authorities and data.

Conclusion

Just like each new technology, NFT has its own advantages and disadvantages for people who use it, especially for artists and creators. For artists who want to join the NFT world, they must understand the mechanisms behind it and weigh their pays and returns before putting efforts into creating NFTs. And hopefully, there will be more regulations and the market could be more mature in the future, which might then actually help artists and the art world.

Bibliography

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Conti, Robyn & Schmidt, John. “What Is An NFT? Non-Fungible Tokens Explained.” Forbes. April 8, 2022. https://www.forbes.com/advisor/investing/cryptocurrency/nft-non-fungible-token/.

Dash, Anil. “NFTs Weren’t Supposed to End Like This.” The Atlantic. April 2, 2021. https://www.theatlantic.com/ideas/archive/2021/04/nfts-werent-supposed-end-like/618488/.

Ellis, James. “Takashi Murakami Flower NFT collection: Everything We Know So Far.” NFT Evening. February 22, 2022. https://nftevening.com/takashi-murakami-flower-nft-everything-we-know-so-far/.

“How Much Does It Cost To Sell NFT Art?” NFT’s Street. May 31, 2021. https://www.nftsstreet.com/how-much-does-it-cost-to-sell-nft-art/#:~:text=The%20site%20takes%20a%2015,passive%20future%20income%20for%20artists.

Kastrenakes, Jacob. “Beeple Sold an NFT for $69 Million.” The Verge. March 11, 2021. https://www.theverge.com/2021/3/11/22325054/beeple-christies-nft-sale-cost-everydays-69-million.

Kinsella, Eileen. “Think Everyone is Getting Rich Off NFTs? Most Sales are Actually $200 or Less, according to One Report.” Artnet. April 29, 2021. https://news.artnet.com/market/think-artists-are-getting-rich-off-nfts-think-again-1962752.

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Technology has always been a really big part of the music business, and has really dictated how we make music, how we consume music.”

Today, NFT probably is no longer a foreign term to many. The digital assets stored on a blockchain have now made their way everywhere, from digital arts, and fashion, to physical event tickets. NFT sales have skyrocketed, especially in recent days. In 2021, the total sales of NFT reached $25 billion in comparison to the total volume of $95 million in 2020. Just in the first few months of 2022, the daily sales in Opensea, an online NFT marketplace, have hit their new highest record. As NFT continues to expand its array of industries, music is no exception to this tremendously growing party. 

Music production and the market are moving fast. While fans constantly accommodate their tastes to fresh sounds on airwaves, artists are also working hard to ride with the latest trends and opportunities. NFTs have the potential to transform the future of music. Their impact is compelling in many ways, including equitable compensation, diverse approaches to NFT selling, and potential profits from the natural appeal of scarcity.

Issues of the music industry

While the global music industry has embraced exponential growth in recent years, artists have encountered unfair payment for their talents. A report from Fortune suggests the typical revenue divide between an artist and other parties is 50/50, with about 50% going to the creator and the rest being split between artists, record labels, agents, lawyers, distributors, and other “stakeholders.” Research further indicates that only about 1% of the artists receive 90% of their streams, and only about 0.8% of top artists can earn about $50,000 per year. Artists find it to be extremely difficult to make a living through their music. Even a fairly successful artist like Daniel Allen, who has his songs playing millions in 2020, receives only a few hundred dollars every month. Apart from this, the label usually holds the original recording of a song, which means the artists only maintain a right to royalties and have absolutely no control over where the music gets to be played. Even when artists are no longer under the label, the company will still hold ownership of their songs.

NFT restores fair payment and autonomy for artists

While artists are struggling with piles of issues, NFT emerged as a new medium to present, market their music, as well as to engage with fans. Music NFTs can take various forms. It can be a song in the form of an audio file or video, an album cover, a concert ticket, merchandise, etc. The unrepeatable music NFTs can be a one-off auction on an audio file or a limited number of copies. Buyers can then store the music NFTs in their crypto wallets. The non-fungible digital files are encoded on the blockchains, such as Ethereum and Solana. NFTs are designed to be unique, immutable, and authentic. Therefore, It gives the artists complete control over how they want their works to be distributed and what rights will be associated with the token by the underlying smart contracts. When artists sell the NFTs, they can decide to preserve all their rights over the creation, as well as the percentage of royalties they want to receive. Once the smart contract is baked into the token, all the terms will automatically apply at every time of future transactions. What it means is that now musicians will have complete autonomy over their creations.

In 2021, EDM artist 3LAU auctioned 33 NFT collectible versions of his album Ultraviolet, which was marked as the first music album to be tokenized. Those NFTs are set to three different levels of rarities, ranging from “Platinum” for the highest bidder to “Gold” for bidders 2-6 and “Silver” for bidders 7-33. Each NFT album also comes with additional gifts, such as a custom song, a limited edition vinyl, or a random selection of 3 NFT songs in the album. It breaks the single NFT record with a total volume of $11.6 million. 3LAU was then joined by artists such as Grimes, The Weekend, and Shawn Mendes. Most recently, Snoop Dogg announced that his former label, Death Row Records, will be an NFT label. In addition, the Kings of Leon was the first band to release an NFT album, featuring tokens of special perks, including special albums, limited-edition vinyl, exclusive art, and front row seats to future live concerts. 

Crowdfunding and fun-based community

Music NFTs open the potential of fan crowdfunding. Musicians can raise funding for songs with simply one social media post. After the pandemic led to a complete halt on live performances, Daniel Allan also turned to NFTs. He managed to raise 50 ETH ($140,000 on the day of trading) in a one-day campaign to crowdfund his upcoming album Overstimulated by auctioning off 50% of his share of future master royalties. He sells songs individually through the NFT music platform Catalog and makes 85% of his living off NFTs. Similarly, Danny Saucedo, one of the most popular Sweden artists, has released multiple singles on his own since he became independent from Sony Music. He raised the same amount he would have from a major label within 48 hours. 

Those successful fan-funding cases reflect a brand new model for the music industry, which has the potential for a drastic change in the industry to be more decentralized and less reliant on the major labels. It becomes possible for artists to gain independence over what they want to create and promote. At the same time, it allows fans to be involved in the creation process in a way they never had before.

Interesting approaches to music NFTs

There are more exciting approaches to selling NFTs. The platform Triptcip allows users to create visualizations for music using a tool called VOID. It makes it easy and fast for electronic music producers to create decent visual content synchronized to their tracks without 3D artists. Another innovative approach comes from the music producer ILLmind. He has launched an exclusive sample pack, which will give the owner “TRUE digital ownership of the pack, backed by blockchain history.”

NFT also provides new ways for artists to engage with fans and broaden their fanbase. Crypto airdrops are a marketing tactic where free tokens from a specific blockchain project will be sent to users. It can increase the awareness of NFT products, reach new audiences, and increase publicity, which will boost the price of a token in return. There are three types of airdrops. Standard airdrops can apply by completing the required information or promotional tasks, such as providing a crypto wallet address to receive the airdrop. Exclusive airdrops are usually reserved for users loyal to a blockchain project. Similar to standard airdrops, bounty airdrops ask participants to complete more promotion work to spread the word about the project, which frequently occurs on social media platforms such as Facebook or Twitter. Holder Airdrops requires participants to have an existing cryptocurrency like ETH or BTC in order to receive the item. 

Other parties sharing the pie

Not only is NFT profitable for artists, but the holders can also benefit from it. The UK-based FRESHA Records released a collection of royalty-share NFTs on some of the label’s biggest classical hits and will further tokenize ten classic singles and two albums on OpenSea. The buyers will be entitled to a 10-year royalty share of an annual rate of 15% net income, excluding publishing. Meanwhile, Relics became the first NFT platform to operate within a record label – Monstercat. The digital collectibles are referred to as “Relic”, which can integrate music in the Metaverse. Users can have them as theme songs in worlds, games, and play-to-earn ecosystems.

K-pop companies have also jumped on the NFT trends. In October 2020, the famous K-pop company SM Entertainment expanded to the digital space with its new “Metaverse Girl Group” Aespa, featuring four human members and four virtual counterparts. In the following year, the company launched a partnership with Binance in developing NFT content. Users will be able to create content in music, game, dance, and goods under SM authorized IPs and earn profits and recognition within the named “P2C ecosystem”. 

Following the steps of SM, some of the top K-pop companies are also working closely with the NFT platform based on their IPs. For example, Kpop Group BTS, in collaboration with Dunamu, launched its own NFT set in the form of photo cards and digital versions of collectible cards featuring BTS members. In a statement to The Wall Street Journal, John Kim, the head of HYBE America’s project, said that “we believe NFTs have the potential for expansion and hope they will provide fans with more varied experiences and opportunities to express themselves.” Similarly, JYP Entertainment also used Dunamu to distribute digital content of its group, including TWICE, Stray kids, Day6, ITZY, 2PM, and its Japan-based group NizuU.

In the meantime, Entertainment companies plan to market NFTs as a channel to interact with their favorite idols beyond being digital collectibles. The Show, a weekly music show based in South Korea, published a set of “The Show FanBox NFT Collection,” featuring short clips of K-pop artists appearing on the show. The fans who purchase expensive items will gain access to The Show’s live performances.

Future for the NFT and music

Like other creative industries, the rise of NFT in the music space is not without concerns. The most potent one will be the environmental burden. Additionally, the NFT music sets a high barrier to many artists, as it prioritizes those who are “tech-savvy, extroverted, and able to be constantly online and releasing content.” And despite the enormous profits NFT is capable of generating, it has not yet been accepted as a mainstream way for people to consume music. In many cases, consumers regard NFT music as a way of investing or supporting those artists they feel are undervalued by the traditional industry. 

Conversely, NFTs demonstrate many attractive propositions: fair compensation and composing freedom, vest kinds of collaborations, and appeals to scarcities and their commercial potential. However, we can be certain that as an evolving technology, it has already changed many artists’ lives. As Daniel Allan puts it: “I felt that a lot of my career was making a certain type of music that I had to make — and at times I didn’t really connect with. From an artistic standpoint, I just feel like NFTs and Web 3 in general can create a much brighter space for art.”

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Fraser, Jake. “How Nfts Could Redefine the Future of the Music Industry.” VentureBeat. VentureBeat, 

February 19, 2022. https://venturebeat.com/2022/02/19/how-nfts-could-redefine-the-future-of-the-music-industry/. 

“The Future of Music NFTS Is Here , It’s Time to Get Involved.” Kulture Hub, March 21, 2022. 

https://kulturehub.com/music-nfts-arrived/.

“How Music NFTS Could Disrupt the Music Industry.” Crypto News, April 5, 1970. 

https://cryptonews.com/exclusives/how-music-nfts-could-disrupt-music-industry.htm.

“How to Create Music Nfts: Guide for Music Producers.” Production Music Live. Accessed April 20, 

2022. https://www.productionmusiclive.com/blogs/news/how-to-create-music-nfts-guide-for-music-producers-2022. 

“K-Pop Groups That Disbanded in 2021 | Allkpop.” Accessed May 5, 2022. 

https://www.allkpop.com/article/2021/12/k-pop-groups-that-disbanded-in-2021.

“NFTs Are One Innovation the K-Pop Industry Doesn’t Need to Get on Board With.” NME, November 

12, 2021. 

https://www.nme.com/features/music-features/nfts-are-one-innovation-the-k-pop-industry-doesnt-need-to-get-on-board-with-3093994.

Stassen, Murray. “K-Pop Giant SM Entertainment Strikes ‘play2create’ NFT Partnership with Crypto 

Exchange Binance.” Music Business Worldwide, February 28, 2022. 

https://www.musicbusinessworldwide.com/k-pop-giant-sm-entertainment-strikes-play2create-nft-partnership-with-crypto-exchange-binance/.

Tengblad, Mattias. “Commentary: Nfts Are Revolutionizing the Music Industry Too.” Fortune. Fortune, 

October 29, 2021. https://fortune.com/2021/10/29/nfts-music-industry/. 

Turley, Cooper. “3LAU Breaks NFT Auction Record with $11.6m in Sales.” The Defiant, September 15, 

2021. https://thedefiant.io/3lau-breaks-nft-auction-record-with-11-6m-in-sales/. 

“Why Nfts and Cryptocurrency Appeal to K-Pop Labels.” South China Morning Post, November 17, 2021. https://www.scmp.com/lifestyle/k-pop/article/3155551/nfts-and-cryptocurrency-draw-k-pop-labels-behind-bts-blackpink.

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. 

Over the past year, there has been a craze over Web3 – while terms like blockchain, cryptocurrency, and NFTs have started to become more commonplace, there is still a deeper rabbit hole of other innovative concepts. In particular, this article will focus on DAOs – specifically, what they are, how they function, how they are currently being implemented, and what the future holds.

First and foremost – what are DAOs? DAO stands for decentralized autonomous organization, and at glance, they are an internet-native group of like-minded individuals that are collectively owned and managed by its members. Generally speaking, they have built-in treasuries that are only accessible by group approval and decisions are governed by voting procedures and proposals.

Before diving a little further into DAOs, it is important to have a basic understanding of smart contracts. At a high level, smart contracts “are computer programs stored on the blockchain that allows us to convert traditional contracts into digital parallels… they behave exactly as programmed and cannot be changed”. This is important because it allows for the creation of a digital marketplace built on automatic, cryptographically secure processes that are stored online transparently. This means that a smart contract will execute on its own when the terms are met, allowing for outcomes to be easily predictable, safe and publicly available.

So what do smart contracts have anything to do with DAOs? In order for a DAO to function, it must be governed by a set of rules that every member abides to – in this case, it is the smart contract. Usually, the contract also includes the definition of their treasury, such that all transactions must be approved by the group, without a central authority (thus, decentralized). Additionally, it ensures that payments are automatically authorized when a vote passes. Finally, since the smart contract is placed on the Ethereum blockchain, it cannot be changed or tampered with by any individual. Below, is a chart that compares DAOs to a traditional organization, provided by Ethereum.org

Although this provides a brief overview of DAOs and what the purpose of the structure is, perhaps the easiest way to gain a better understanding of how they function is to explore case studies of how DAOs are being used today.

Case Studies:

First and foremost, we’ll take a look at dOrg, one of the first DAOs to be legally recognized as a LLC within the United States. Within an article detailed by TIME, several members of the DAO spoke to how their company differs from traditional LLCs. First and foremost, co-founder Ori Shimony describes that there are no general management positions (e.g. CEO, CFO) and roles are fluid, such that individuals have different jobs dependent on the project they are currently working on. Additionally, everyone who officially works at the company owns a share of its LLC and all company decisions are made based off of a voting procedure using tokens, which are given to members as they complete projects. While this may sound atypical and off-putting, members within the team explain that for the first time they have real ownership over their work, and the non-hierarchical structure of the company allows for specialists to take on leadership positions when the project requires it, allowing for multiple people to provide guidance and direction. Additionally, since DAOs function remotely, it allows for team members to have more autonomy over their work schedules and hours. Finally, dOrg is also transparent with their salaries with “all salaries and budgeting are publicly maintained on the blockchain; payout logs are visible to each member”, and each member has the option of being paid in cash or tokens. This is probably the gold standard of what Web3 enthusiasts envision DAOs to be and how they can disrupt traditional company structures.

Having said that however, DAOs can vary in many shapes and forms – what is definitively a DAO can be very confusing and its legality can also be called into question. Perhaps one of the most popular DAOs today is ApeCoin DAO. With the recent release of the Otherside NFT that exclusively accepted $APE, we saw prices skyrocket all the way to an all time high of $26 with a market cap of almost 7 billion dollars. The DAO’s membership is simple – holding any ApeCoin provides membership in the DAO, which allows for participating in idea and proposal submissions in addition to voting rights. While we haven’t explored DAOs that are based on tokenomics, this is something that is commonly seen with Web3. Details regarding the governance of the DAO along with proposal processes and voting mechanisms are described in higher detail on their website. More importantly however, is understanding some of the mechanics that make ApeCoin DAO different to other DAOs. First and foremost, 62% of the ApeCoin fund was distributed to holders of the BAYC/MAYC NFTs. Secondly, ApeCoin is tradable on Coinbase, FTX, along with a variety of other large exchanges, despite not being legally registered with the SEC. And finally, the APE foundation, led by Alexis Ohanian (Co-founder of Reddit), is a legal entity that “administers the decisions of ApeCoin DAO”. These differences have caused some to raise eyebrows surrounding the DAO. Under the guise of tokenomics and a DAO, $APE is not a security, despite having “stock vibes“, the DAO never promises profit to holders and states that “One APE equals one APE” and acts as a utility token as in-game currency for Animoca Brands’ Benji Bananas. While this may cause some to be concerned, SEC regulator William Hinman explained in 2018 that if something is “sufficiently decentralized,” it may not be considered a security. Having said that, ApeCoin DAO is comparatively very centralized – not only does it have a foundation that serves as the administrators for the DAO, but BAYC/MAYC creators, Yuga Labs, have a heavy hand in shaping the utility of the token. This unique study gives interesting insight into how legality plays a role into this new organizational structure, along with some of the current flaws in the system that allows for gray areas.

Since DAOs are still relatively new and in the process of being defined, many have already started to explore implementing DAO-like structures into their projects through NFTs.

Perhaps the most notable example is Bobu the Bean Farmer. The “experiment’ explores decentralized IP management, and rather than using a custom smart contract just for a DAO, they operate by creating a tool used for decentralized voting through ERC-1155 tokens (a type of smart contract token used for NFTs). The project operates under many of the same guises and systems seen across many other DAOs, including a governance model that utilizes a multisig wallet that will require multiple members to sign off on transactions, proposals that require governance voting, and a committee that will decide which proposals will be voted on. While many of the core concepts are not original to Bobu, it is the only one that is doing so through an NFT and characterizes members through holders of the Bobu NFT token. Additionally, rather than having a smart contract that onlines voting procedures, currently, votes are held on Discord, which is far from being a decentralized system. Additionally, the Azuki team (the creators behind Bobu as well as the extremely popular Azuki collection) has the power to intervene on Proposals, as well as will be releasing a timeline, schedule and planning the general direction of the project. Although the project itself never identifies as a true DAO, it is interesting to see how NFT projects are taking these concepts and applying them to different areas within the Web3 space.

Another atypical example of a “DAO” is Proof Collective. Having recently launched their Moonbirds collection, they have been receiving a lot of press giving their extreme demand in the secondary market that has racked up over $281 million. While not officially labeled as a DAO, Proof Collective is a group of 1000 NFT collectors, and includes well known figures in the space, including Mike Winkelmann (or Beeple) and Gary Vaynerchuk. Although they are not governed by smart contract, membership to the organization can be bought through owning a Proof Collective membership pass, which originally sold for 1.99 ETH and currently resells for ~100 ETH. Additionally, members are given access to exclusive drops from the brand as well as early access to future releases. Having said that, these are features commonly found within other NFT projects.

The Future:

After studying a couple of examples of DAOs, it is possible that you may feel even more confused than before – unfortunately, given how new all of Web3 and blockchain technology is, this is the reality of the situation. Although many are enthusiastic about the potential of DAOs, such as this Harvard Business Review that echoes many of the points made by dOrg members – notably that DAOs allow for individuals to have more autonomy over where, when and how they work, more freedom to pursue more fulfilling projects, more decision-making power, ownership and transparency with compensation – there is also a lot of uncertainty with how these organizations will operate legally as well as the direction and future of how they function. Whether or not they continue to operate using more traditional tokenomics or NFTs is still yet to be seen and the line between what is considered a DAO and what is not is still currently being built and developed as we watch the world of Web3 continue to grow.

Bibliography

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• “Azuki.” Bobu The Bean Farmer, https://bobu.azuki.com/governance. 
• Chow, Andrew R. “No Bosses: What It’s like Working at a Dao.” Time, Time, 24 Mar. 2022, https://time.com/6146406/working-at-dao-dorg/.
• “Decentralized Autonomous Organizations (Daos).” Ethereum.org, https://ethereum.org/en/dao/. 
• “Ethereum’s Russian-Born Cofounder Has Been Quietly Supporting a Dao That Raised $8 Million in Crypto for Ukraine. His Dad Is Even More Involved.” Yahoo! Finance, Yahoo!, https://finance.yahoo.com/news/ethereum-russian-born-cofounder-quietly-183929743.html. 
• Glaveski, Steve. “How Daos Could Change the Way We Work.” Harvard Business Review, 7 Apr. 2022, https://hbr.org/2022/04/how-daos-could-change-the-way-we-work. 
• Locke, Taylor. “Russian-Born Ethereum Co-Founder Vitalik Buterin Quietly Donates $5 Million to Ukraine Relief Efforts.” Fortune, Fortune, 8 Apr. 2022, https://fortune.com/2022/04/08/vitalik-buterin-ukraine-donation-ethereum-russian-invasion/. 
• Locke, Taylor. “What Is the Moonbird NFT Collection, and Why Did It Surge so Quickly?” Fortune, Fortune, 19 Apr. 2022, https://fortune.com/2022/04/18/moonbird-nft-collection-surge/. 
• Lopatto, Elizabeth. “Will APECOIN and Yuga Labs Make the Regulators Go Ape?” The Verge, The Verge, 25 Mar. 2022, https://www.theverge.com/2022/3/25/22994795/apecoin-yuga-labs-sec-regulation-utility-token.
• Roose, Kevin. “What Are Daos?” The New York Times, The New York Times, 18 Mar. 2022,
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• Tan, Eli. “YouTuber Logan Paul Files Trademarks for NFT Marketplace, Dao Ventures.” CoinDesk Latest Headlines RSS, CoinDesk, 10 Feb. 2022, https://www.coindesk.com/business/2022/02/10/youtuber-logan-paul-files-trademarks-for-nft-marketplace-dao-ventures/. 

What is NFTs?

“NFTs are tokens that can signify ownership of individual items. They permit us to tokenize objects such as art, collectibles, and even property. NFTs could only have one legitimate owner at a time and are protected by the Ethereum blockchain; no one can alter the possession record or create a new NFTs. The abbreviation NFT stands for non-fungible token. The economic term non-fungible could be used for your furniture, a music file, or your computer. These goods cannot be substituted for others due to their distinct characteristics. In contrast, the exchangeability of fungible goods is determined by their value, not their distinctive qualities. ETH and dollars, for instance, are fungible because 1 ETH / $1 USD can be swapped for 1 ETH / $1 USD.”

No two NFTs are identical from a digital standpoint. Every non-fungible token is required by one owner, whose identity is public record and easy to identify. NFTs are interoperable with anything produced on the Ethereum blockchain. “A ticket issued in the form of a non-fungible token (NFT) can be exchanged for a different NFT on any Ethereum marketplace. One could exchange a work of art for a ticket. Creators of content are able to reach a worldwide market and sell their work anywhere. Creators can keep ownership rights over their own work and receive royalties from resale transactions directly. Uses for objects can be unexpected. In a decentralized loan, for instance, digital artwork can serve as collateral.”

How NFTs change the Art industry

Nowadays, NFT has evolved as a technology that can conclusively verify the authenticity of the original digital artwork. The artist can generate a non-fungible token (NFT) for his digital art, which will produce an unalterable and irreversible record on the Blockchain, certifying the art as original and one-of-a-kind. This artwork can also be monetized through NFT by the artists. Using NFT marketplaces, he can sell his NFTs straight to a buyer.

Accessibility

NFTs help makes it easier for beginners and customers to enter the market. For instance, an unnamed 12-year-old can create NFTs of pixel whales. And, he also managed to sell them online for over $400,000. On top of that, people all over the world are buying these whales. When it comes to traditional art, only a few communities have access to these paintings, which are mostly sold at auction houses. Compared to traditional markets that are difficult to access, NFT art is global and accessible to everyone.

Transaction

“NFTs have revolutionized the way transactions are done in an industry that is largely unregulated given the amount of money flowing through it. Because the blockchain network creates a permanent record of all transactions related to a particular NFT, NFTs are able to bring change to this largely unregulated space. In doing so, the blockchain creates a contract, called a “smart contract,” which is protected by cryptography. The contract contains information about the primary market for NFTs, including the creator and first purchaser, as well as information about their subsequent changes in ownership and valuation.”

Transparency

This information’s accessibility to the public enables the development of a decentralized and transparent marketplace for artists. This is in stark contrast to the traditional art market, which has prospered without transparency, with commercial galleries, dealers, and auctioneers capturing the majority of revenues. With the emergence of NFTs, artists, particularly underrepresented ones, have discovered equitable opportunities by obtaining pricing and supplying information pertinent to their artwork in exchange for certifying it on the blockchain. Collectors also benefit from the system because they can verify the authenticity of dealers and compare pricing.

NFTs Application in Art Industry

NFTs are widely used in different artistic fields, such as painting, photography, and music production. Here are some examples:

The combination of painting： “Everydays: the First 5000 Days” is a digital artwork produced by Mike Winkelmann, also known as Beeple, and depicting the first 5000 days of his life. The piece is a collage of 5,000 digital pictures that Winkelmann generated for his Everydays series and assembled into a single composition. In 2021, the non-fungible token (NFT) connected with it sold at Christie’s for $69.3 million, making it the second most valuable non-fungible token on the market.

The photo “Love is War” created by Aimos Vasquez is sold for $125,000 which means 40ETH.

Music NFTs sold by Grimes and Steve Aoki are worth millions. Grimes made $6 million in 20 minutes thanks to Gemini’s NFT marketplace, Nifty Gateway. With the sale of a collection of ten exclusive digital artworks, which included some that featured original music, the Canadian singer made $5.8 million. WarNymph Collection, Vol. 1 was the title. Steve Aoki, an electronic DJ and producer, released his first NFT album, Dream Catcher, a week later on the same site. For $4.25 million, it was sold Antoni Tudisco, a renowned visual artist, collaborated on Dream Catcher’s 11 distinct artworks. Unique sound effects and visually stunning animation rounded out the package. The Weeknd (whose NFT collection sold for $2 million) and Eminem (who made $1.78 million from his first collection of NFTs) were able to make seven-figure sales on the platform because of their early sales.

NFTs Royalty

As we all know, royalty is a very important thing for artists, and NFT happens to give artists a good guarantee on the issue of royalties.

A part of the sale price of your NFT creation is paid out to you as NFT royalties. Smart contracts perform NFT royalty payments on an ongoing basis. You have a lot of options when it comes to marketplaces, including the ability to customize your royalty portion. A normal royalty is between 5% and 10%. For instance, In February, when “Crossroads” by the digital artist Beeple was resold on the secondary market for $6.6 million, more than 100 times its original sale price, Beeple received a 10 percent royalty from the transaction.

Another example is how difficult it is for most musicians to earn money in the age of streaming. Artists get cents per stream and must maintain or cultivate a significant audience in order to make a living. According to data from 2019 and 2020, ninety percent of live streaming went to the top one percent of performers. Even a modestly popular musician like Daniel Allan, whose songs received millions of listens in 2020, can only make a few hundred dollars a month from streaming, which necessitates He supported himself by mixing and mastering the music of other artists. Allan has been selling digital versions of his electro-pop tunes in the form of NFTs (non-fungible tokens) for thousands of dollars apiece, because of the influence of COVID-19. In addition, Allen’s use of NFTs enables him to collect more royalties than record labels and streaming giants. NFT provides musicians with greater independence and financial support from fans, as well as greater communication with followers. NFTs are a breakthrough for artists who are being squeezed by brokerage businesses, in my opinion.

NFTs Art Market

At a cumulative annual growth rate (CAGR) of 52.1%, the global market for non-fungible tokens is anticipated to increase from $14.02 billion in 2021 to $21.33 billion in 2022. At a CAGR of 40.2%, the market is estimated to reach $82.43 billion in 2026.

According to some industry sources, sales of art and collectibles through non-transferable titles exceeded $23 billion. In the last year, the size of the NFT art market expanded by $41 billion. It can be seen that people still have great enthusiasm for the NFT art market.

The non-fungible token (NFT) market is predicted to increase by $147.24 billion between 2021 and 2026. Over the forecast period, the market is expected to develop at a strong CAGR of 35.27 percent. This increase can be attributable to an increase in demand for digital artwork. However, uncertainty in the NFT sector may stifle growth in the next years.

NFTs Future Prediction

NFTs is still a controversial topic. Some people think that NFT is just a short-lived trend. In other words, it is a manifestation of people trying to catch up with the trend. Some argue that the energy use and carbon emissions associated with their use offset any potential benefits they might gain. However, many others believe they bring value and innovation to many different industries, from the obvious (like gaming and anything involving the metaverse) to less obvious use cases (like real estate, healthcare, and insurance. Although NFT is now widely used in the field of art, it is expected that we can see some new applications in the future, such as in restaurants. An entrepreneur is constructing a restaurant where NFT ownership is necessary prior to dining. The NFT will grant consumers access to the restaurant in 2022, which will have a cocktail bar and a private dining experience. Vaynerchuk is hardly the only restaurant that is experimenting with digital cuisine. Red Rooster in Harlem, which is owned by celebrity chef Marcus Samuelsson, is also exploring the space. He produced an NFT that can be redeemed for a private supper for four, along with a piece of art that ingeniously depicts the chef’s fried chicken. Like many chefs, Samuelsson hopes that the culinary arts will not be left behind in the world’s digital transformation.

In the end, let us look forward to the future development of NFTs jointly.

Bibliography

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Identifying Key Terms

The main technologies for data analytics that I will be looking at are centered around artificial intelligence (AI), predictive analytics, and the use of big data. AI involves the use of machines to mimic the actions and decision-making processes of humans. AI is helpful in that it is able to identify patterns that emerge from data. The end goal of predictive analytics is to predict future outcomes; these outcomes are predicted using past data, machine learning, and algorithms. Big data is tied to both predictive analytics and AI, and generally refers to big amounts of complex data that can be analyzed for producing insights. Most of the examples found through my research involve a combination of these three processes for the purposes of assisting operations.

Arts Nonprofit Organizations

Arts nonprofits can use (and have used) data analytics and AI for assistance in internal operations. Museums specifically have been encouraged to utilize data analytics as a way of creating cases for support to existing and potential funders, and as a result, maintain relevancy for future museumgoers. AI and machine learning have both been utilized by nonprofits in general as a way of encouraging fundraising. GiveCentral suggests creating an algorithm that looks at data from funders as a way of being more in touch with donors. Similarly, AI can be used to quickly identify both individuals who are more likely to donate, and recently lapsed donors. In addition to fundraising, these technologies can also be used for general administrative tasks. Machine learning can be used for tracking data, rather than having a human employee do it. The use of chatbots for daily interactions with customers can also be helpful in making sure that employees can direct their attention elsewhere. When it comes to marketing, AI and machine learning is described as being able to help an organization develop better marketing strategies by analyzing data from different regions. While “traditional arts centers” may not be as advanced as digital platforms in their usage of data and data analytics, institutions such as the Mondavi Center for the Performing Arts in Davis, CA have used data for  creating socially-distanced seating models, predictive pricing, and profitability.

Aside from instances where AI has been used in both creative processes and in the restoration of art, these technologies have also been utilized for audience-facing experiences. This technology, while in some cases adds to the audience member’s experience, also helps management in the long-run by providing the institution with more interpretable data. It is worth noting that the visual arts world seems to have more pertinent examples of usage compared to the performing arts. One use of AI/machine learning has been deployed to predict the amount of time that an audience member will spend looking at a specific exhibit; the data helps the museum understand which exhibits attract the attention of audiences the most. Maintaining and understanding the interests of audiences is part of the ongoing work of a museum; the National Gallery in London, UK, utilized big data and machine learning for understanding the experiences and visitors as a way of “forecasting future engagement.” Similar institutions such as the British Museum have interpreted big data for the purposes of better understanding visitors and designing exhibits and programs that are more aligned with the interests of their patrons. The British Museum collected data from “audio guides and interactive exhibits” with the consent of visitors. In a slightly less clandestine way of collecting visitor feedback, many Swiss museums have used an app where visitors are able to share their experiences with museum directors directly while they are walking through the museum, as opposed to a completing a post-experience survey.

Entertainment & Sports Industries

There are significant uses of data analytics for the purposes of understanding and retaining audiences in the nonprofit arts, and within the larger media & entertainment industry, there seems to be an even larger emphasis placed on this. AI, predictive analytics, and big data are all utilized for the purposes of attracting customers, understanding what audiences like and dislike, and personalizing content for individual customers. Broadway uses a predictive analytic, big data utilizing software called PatronLink360, which is designed to assist in audience attraction and subscriber retention. In the film industry, executives have utilized big data as a way of better understanding what audiences do and don’t like in order to develop both creative and marketing strategies, and predict what audiences might be interested in. AI and predictive analytics can be useful in the process of personalizing content suggestions. One of the most prominent examples is through streaming sites such as Netflix; data on previous viewings are analyzed through AI and machine learning to give the customer suggestions on what to watch next. The common idea is that personalization can serve as an effective way of retaining customers, and as a result, creating a sense of loyalty. However, there are most likely other factors that play into whether a customer chooses to maintain a subscription beyond the content that is made available (such as pricing).

Aside from using these technologies for improving the performances and nutrition of athletes, and management of personnel, the sports segment of the entertainment industry uses AI and big data in ways that are similar to the arts, especially as it relates to the overall fan experience. The sports industry in general places a large emphasis on the relationship with fans. By looking at social media, in addition to attendance records, teams can use big data to understand fan sentiments and create marketing strategies as a result. Teams and stadiums have used data to analyze merchandise sales, and to see which events are more likely to sell higher numbers of tickets. With regard to ticketing, some teams, such as the soccer team Columbus Crew, have used facial recognition in place of utilizing physical tickets for entry. Additional examples of current uses of AI include facilitating stadium entry, and, similarly to some arts organizations, chatbots for customer inquiries. An example that is used in sports that has not been seen in other examples is the usage of data to analyze day-of conditions (including the weather) as a way of better preparing staff and management for the event. Aside from the facial recognition-ticketing, it seems like it may be difficult to utilize AI when attending a sports event in person; however, AI can also be used for advertising and adding to the viewing experience for people who may be watching at home.

Takeaways and Points for Consideration

One of the main similarities that I saw across these leisure industries was that the customer is generally at the forefront of consideration. These respective industries all have the goal of attempting to better understand their customers/patrons and effectively market to them, while also making sure that their audiences have a beneficial experience. A similarity between the nonprofit arts and the sports industry that I found both interesting and unexpected was the utilization of chatbots. However, it makes sense considering that both of these industries place a large emphasis on ticketing and making sure that the customers’ needs are met. A key difference is how nonprofit arts organizations have an added aspect of fundraising and developing/maintaining relationships with donors in their operations. Overall, there were more similarities between these industries than what I had initially expected. However, it seems that there are still differences in the scales at which these technologies are implemented.

Some of the implications or things to consider focus on the idea of big data, and data utilization in general. In order to derive results on audience insights, for example, an organization has to obtain a significant amount of data that is actually worth paying attention to and making decisions off of. Additionally, successfully implementing these measures requires a fair amount of both time and training. Arts nonprofits—and businesses across other industries—should consider what their organizational capacities are prior to delving in to large-scale changes that involve these technologies. At the same time, it is very possible to develop and utilize chatbots as an ‘introduction’ to incorporate AI and data. Lastly, when it comes to the collection of data, one aspect that actors across all industries should be aware of is increasing concerns over data privacy and recent laws regulations that require companies to protect personal data, such as the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). A recommendation is for businesses to consider these public policies and any new developments surrounding data compliance.  

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Rossow, Andrew. “The Birth Of GDPR: What Is It And What You Need To Know.” Forbes. Accessed May 6, 2022. https://www.forbes.com/sites/andrewrossow/2018/05/25/the-birth-of-gdpr-what-is-it-and-what-you-need-to-know/.

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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

Australian Government. 2014. “Privacy Act 1988.” Legislation.gov.au. Attorney-General’s Department. March 12, 2014. https://www.legislation.gov.au/details/c2014c00076.‌

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/.‌

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Walking into a museum, what is your likelihood to go straight to the console and make a donation? The chance is pretty slight. Research in museum fundraising studies has shown that donation does not come naturally, rather it needs to be nurtured. No matter how large or how small the donation is, it requires the institution’s long time commitment to building relationships with the donors. Museums around the world pull out all the stops to solicit donations, from holding fashion galas to special tours from curators and directors. For instance, Tate Modern the national modern art gallery in the U.K. has designed a multi-leveled annual membership program that provides a wide range of special activities for different levels, from special culture tours to artist studio visits. 

• Young Patron (aged 18-40) (It is interesting to call a 40 years old successful businessman “young”. I guess you can tell how the museum is facing the aging problem)  
  • Annual fee £1,200 (fully tax deductible)
  • being part of a sociable group with a contemporary focus
• Silver Patron 
  • Annual fee £1,500 (fully tax deductible)
  • explore the UK’s diverse cultural landscape from the historical to the contemporary
• Gold Patron
  • Annual fee £6,000 (fully tax deductible)
  • get to know the London and European art scenes with insights from Tate’s directors and curators
• Platinum Patron
  • Annual fee £12,000 (fully tax deductible)
  • premier access to Tate’s directors and curators, high-profile artists, leading collectors, and art specialists in the UK and internationally

According to the published list of patron names, the length of the list remains stable in the past decades. When the development of personal relationships is required in every case, the growth is strictly limited by the capacity of staff in the museum development department. Being one of the most reputable art museums in the world, Tate modern worries little about not attracting enough funds for operation. However, thousands of much smaller museum does. Many struggles to source locally and the donor groups are facing elderly problems. Solicitation donation is a social business and a patron base lie at the core of it. Many museum’s core donation groups are growing old with the museum and there’s no young blood flowing in. The entire art world is facing similar pressure. Strong art buyers are still real estate tycoons and rich bankers. However, technology companies are rising to become the most lucrative business and money flows to young tech start-up entrepreneurs. From historical data, we can tell they are not followers of the traditional art patron path. Museum’s traditional fundraising solicitation method is doing very little for the new middle class.

The digitalized platform can scale this social business with marginal costs lower than ever before. Experiences from the fast-growing gaming industry can be applied to museum patron programs as well. The young generation could find their sense of belonging, community, and accomplishment in a game. The museum can utilize their behavior habit to design patron experiences more appealing to the younger generation. Coachella and LV’s transformation to the gamified online rewarding programs are two successful examples of attracting young, rich, and vibrant audiences, those museums should target as well.  

Coachella, an annual music and arts festival held in Colorado Desert started in 1999, realized growth from 250,000 attendance in 2017 to 750,000 attendance in 2022. About 25% of attendees had a household income of $100,000 and 68% of them were aged between 15-29. The ticket price ranges from $400 to $9,800. Compared to the museum donors, the contributor group of Coachella is no less rich and much younger. One of the key elements of keeping vibrant is communicated in young people’s language, such as being a harbinger to adopt gamification interaction to boost engagement. In 2019, Coachella introduced Coachella Coin, an interactive game on the festival’s smartphone app. The game provides an in-depth scavenger hunt, a special world map, and virtual currencies that could be exchanged for a ride on the Ferris wheel, blankets, scarfs, pins, and drinks. By making the festival and video game experiences overlap, Coachella augmented reality into a real-life video game.

In 2022, Coachella leveled up and went all-in with augmented reality, gamification, and NFTs. The festival offered every paying attendee a free In Bloom NFT that will grow and unlock special benefits, such as VIP upgrades, 2023 weekend passes, Goldenvoice concert tickets, and Ferris wheel rides. Besides ticketing purposes, there are different collections of NFTs one can purchase to be redeemed for tangible items. The Sights and Sounds Collection featured 10 photos that came with exclusive soundscapes from the polo field and were limited to 10,000 NFTs that sold for $60 each. The Desert Reflections Collection created by artist Emek could be redeemed for a physical photo book of the festival and was limited to 1,000 NFT for $180 each. The most expensive NFTs were part of the Coachella Keys Collection grating lifetime passes to Coachella in April every year and were limited to 10 NFTs. Each sold in the six figures, with a total coming to $1,474,000. All of the NFTs were sold out shortly after going on sale. 

Another case is LV’s 2 million downloads NFT Game, celebrating its 200 year anniversary. The game starts with the Louis Vuitton family story and introduces participants to the legend and history of the brand. The avatar character, Vivienne, gives the audience a request to collect NFT postcards and travel to different locations in glamorous cities such as Paris, London, Los Angeles, and more. The game has stirred a lot of response and community engagement all over the world, especially with the brand followers and customers. This experiential digital game differentiates from traditional magazine advertisements in ways that it tells the story in young consumers’ language. LV is not the only luxury brand adopting gamified digital experience. Italian label Cucci embedded its iconography into consumers’ memories through a gamification effort found within its mobile application. Players were tasked with memorizing new brand motifs as they customized a digital Dionysus handbag, spurring product awareness. Teaching heritage through gaming is effective and can apply to museum studies. 

Here I present a new business model for gamified patron program for museums: 

Customer Segments

This program is designed for museums to target individual donors. So the two customer segments are museums and donors. Target museums are those willing to gain more funding from individual donors, expand their donor pool to the younger generation, and boost the efficiency of their marketing effort. Donors are entirely attached to institutions and managed by the museum.

Value Proposition

1. Donors: By establishing clear goals and quests, gamified patron programs can help donors gain a sense of accomplishment throw contributing to the museum. Secondly, a reward system can create a positive feedback loop to allow donors to take more initiatives in being part of the museum community and make themselves widely known to the art world. Thirdly, the community created by the online system can give non-local donors into the same conversation and take a more active part and more sense of ownership over the money they donated. Fourthly, information could be tailored to be more exclusive and direct than monthly donor emails. More diverse community special benefits could be executed as well. 
2. Museum: Applying a digitalized patron system could reduce the average cost of soliciting each donation, especially for small donors. Currently, staff in the development team could hardly focus a lot of time on small donors. 80% of the donation very likely comes from 20% of the top donors. It is a good strategy to give up the 80% small donors and more on the 20% big donors, because no matter the size, the effort to solicit each donation has no big difference. By embracing gamified patron program, staff can still focus on building a personal relationship with the big donor and let the digitalized system works with the small donors. This digital system could help museums gain more behavioral data on their targets and apply machine learning models to predict and more accurate response to their needs. This decentralization of data empowers museums with more control of ver their targets and improves performance. Thus, a larger customer group can be reached and more funding to gain. 

Key activities

Moving hierarchy of different levels of donation online with addition to quest, points, reward, and community. Setting a goal and a storyline that ties to the interest of donors and museum exhibitions. This could make boring knowledge fun to learn. Moreover, introduce players to customized avatars and encourage them to present themselves in the community. Different levels of customers will have different activity loops. One of the most important elements is the sense of community. Through learning the behavior of donors should the system classify them into different groups and feel they are surrounded by those they respect and feel comfortable talking to. Inside the community, museums can insert evaluative tools to gain more feedback and give patrons more sense of participation. Moreover, user-generated content can free conversation between artists and the market as well. This sense of community can only be established through a digitalized and gamified patron program and machine learning of data. 

Conclusion

It is urgent for museums to seize those opportunities and kick start a double growth curve in the art market. Online exhibitions attract little audience due to the lack of special occasions. Currently, most patron connection starts locally. One finds information about an interesting exhibition and walks into the museum, leaving your email address when buying a ticket online. Several days later, one receives an email about the new exhibition and another one. And the next year, one receives a solicitation email asking for a donation for a special program and that email goes straight to the trash bin. The experience and the return of donation are not very appealing. Through a gamified membership program, the museum can build a community through much richer interaction.

It’s time to move. 

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