Emily Ratajkowski minted an NFT called “Buying Myself Back.” The NFT was sold by Christie’s Auction House for $175,000.

The swimsuit image of Ratajkowski is from Sports Illustrated, which owns the image. The Instagram post wall hanging is actually a piece by artist Richard Prince, who Ratajkowski criticized for stealing her image without permission. The overall image of her standing in front of the piece is the NFT itself. The NFT is Ratajkowski’s statement of ownership involving two pieces that she legally does not own the copyright to.

“Buying Myself Back” is both a statement on the lack of autonomy models have over their own image and a perfect metaphor for the layers of ownership and copyright issues involved in the sphere of NFTs. The question is: Could Sports Illustrated take legal action for Ratajkowski’s resale of the image? Could Richard Prince? What would it look like if they did? And would Christie’s hold any liability?

Digital Ownership

Non-fungible Tokens or NFTs have taken the world by storm over the past few years. As NFTs skyrocket into a common commodity, legal issues are already rearing their heads. The selling promise of NFTs providing enhanced digital ownership brings with it both exciting opportunities and legal confusion. NFTs provide a framework to understand how our current Intellectual Property and Copyright laws might not be suitable for the new web 3.0. How arts organizations navigate these dilemmas may be crucial as the first wave of NFT litigations make their way through court.

The culture of the NFT landscape is imbued with an air of invincibility, especially around ownership. While many may consider NFTs a wild west, free of penalty, it may just be because we haven’t established the laws that will restrict and hold accountable those dealing in NFTS. As we see these issues making their way into both the public and legal spheres, it’s time to rethink key stakeholders’ roles in the process and how they might be implicated in legal spheres. Some of the most highlighted issues we are seeing are Intellectual Property ownership and blatant art theft with NFTs. 

Timeline of some key NFT ownership lawsuits:

These cases are still working their way through the legal system, and their outcomes will be telling about how we will manage ownership issues and NFTs in the future.

U.S. Copyright Code: Does it fit on the blockchain?

To give some insight into the current legal infrastructure these cases are built around, I will outline some of the key sections of United States copyright law that come into play here.

The key laws surrounding the issue of ownership and NFTS fall under Title 17 of the U.S. Code, which enforces copyright. Specifically sections 109, 106, and 504 are relevant to this discussion.

U.S. Title 17, Section 109 is also known as The Right of First Sale doctrine. It established that, should someone purchase a physical object, let’s say a painting, from the creator, they legally do not have to obtain permission from the creator in order to resell or do what they wish with the object. Digital objects are a different story. In 2001, the United States Copyright office offered the opinion that the Right of First Sale could not apply to digital objects (as they are inherently copies of an original), and this opinion was confirmed in Capitol Records LLC vs. ReDigi Inc in 2013. An individual who purchases a digital object is not, by law, entitled to its ownership inherently. So what does this mean in the context of NFTs, whose existence on the blockchain is supposed to represent unique and exclusive ownership? This is where things get muddy.

Section 106 outlines the exclusive rights of the copyright holder. These are: 

An individual who creates a piece of digital art is entitled to these rights surrounding their art. When it is minted as an NFT and sold, these rights are not automatically transferred to the buyer. Much of the confusion surrounding NFT ownership comes in here: many buyers believe that purchasing the work also entitles them to these 6 rights of ownership.

One example of such confusion is Spice DAO’s purchase of an NFT unpublished manuscript of Dune. Shortly after the 3 million dollar sale, Spice DAO tweeted what they would be doing with the copy, including making it public and using it for other projects. However, as the original creators later made clear, they were not entitled to publicizing or recreating it just for buying it. The only thing they got from the sale was personal access to the manuscript. Because the original creators remained the copyright holders through the transaction, they are still the only ones entitled to the rights. Despite the mockery Spice DAO faced on Twitter for this misinterpretation, it does reveal how people think about what they are entitled to when they purchase an NFT.

Some lawyers in the blockchain sphere believe our copyright laws should evolve to recognize the buyer of an NFT as the legal copyright owner. But what might that mean for artists whose work is stolen and resold as NFTs? Could this be a viable change before we have established more protection for artists?

Art Theft, Opensea, and DeviantArt

One of the major issues in the scope of NFTs right now is art theft. Despite the fact that the NFT marketplace creates contract systems under which artists can collect royalties on resales of their work (a huge milestone for visual artists) when it comes to art theft, this system can become much more dangerous. In order to mint an NFT on platforms like Opensea, a user does not have to prove identity, just has to have a crypto wallet. The person creating the NFT simply uploads a JPEG and then mints it at their own set price, with their own stipulations on its resale and the rights that come with the NFT. It gets sold, and then resold.

Many cases have been surfacing of artists finding their original artwork being sold for thousands of dollars on the NFT marketplace without their permission. A Banksy copycat made out with $900,000 in lookalike NFTS. Deceased artist Qinni’s work was reproduced and sold shortly after her death as NFTs.   With little legal and financial recourse, artists have started to depend on one another to monitor the marketplace for stolen art. A Twitter account, @NFTtheft, exposes and reshares stolen art NFTs and asks followers to mass report the fraudsters. 

Part of this issue, as I mentioned, is the lack of verification needed to actually mint an NFT. The other part is that platforms like Opensea and Rarible do little to prevent it from happening again. Let’s say you are a digital artist and you see your art on Opensea being sold for thousands of dollars. You can report the user, verify your identity and proof of ownership, and Opensea might take the fraudulent account down. Little ensures the fraudulent account owner won’t just create another account and do the same thing again. On top of that, the original artists cannot claim any of the profit made by the scammer, and Opensea doesn’t retrieve any of that profit. 

This system also poses threats to NFT buyers. If someone, even unknowingly, resold a stolen image, they would be held liable should this issue go to court. Violating someone else’s copyright, whether intentional or not, could result in damages of $750-30,000 per infringement should the issue ever be seen in court. The risk this poses to NFT collectors shouldn’t be overlooked, and it is something anyone purchasing an NFT should consider before buying.

One platform is trying to change this. DeviantArt, the world’s largest digital art platform, has developed an AI system that scans both its website and NFT marketplaces to find matches. When a match between the DeviantArt site and NFT marketplace is found, it alerts the original artist on DeviantArt that their work is being sold as an NFT. According to DeviantArt, “infringement related to art theft bot attacks dropped over 600%” since their initial launch of the program. 

Implications for Arts Organizations

Art museums, galleries, and auction houses have been getting in on the NFT game. Most notably, Christie’s NFT auction in 2021 ended in over 3 million in sales. The Dune NFT was purchased through Christie’s auction. So, assuming that it is possible for stolen art to be sold as NFTs through the platform of a Christie’s auction, could Christie’s be held liable? And what responsibility does the art organization have to protect both artists and buyers?

Legal responsibility in situations like this is quite layered. If you were to buy an NFT from a Christie’s auction, you would directly or indirectly be dealing with: (1) the original NFT creator, (2) Christie’s, (3) the NFT marketplace such as Opensea, and (4) a cryptocurrency wallet application. Christie’s Auction House has a Terms of Sale document, Opensea has a Terms of Service agreement, and the Crypto Wallet where the exchange takes place has a Terms of Use policy. Also, the NFT itself may be coded with both a Smart Contract and a License Agreement. Which links of this chain should be held responsible for art theft?

Take Christie’s Conditions of Sale, for example. The document is 31 pages long and contains one small paragraph on the sale of NFTs, which states “we expressly disclaim all implied warranties as to the NFTs, including, without limitation, implied warranties of merchantability, fitness for a particular purpose, title and non-infringement. We cannot and do not represent or warrant that an NFT is reliable, current, or error-free…” 

It begs the question of whether we should be asking for more accountability on the part of the art organization, the NFT marketplace, or both. What we might be seeing in the future is more vast applications of AI such as DeviantArt Protect in order to protect actual arts organizations from liability, and for them to protect the artists they represent. In many ways, as legal precedent is awaited, it is up to the arts organizations to decide what role of responsibility they play when it comes to intellectual property and copyright threats with NFTs. If the medium of sale is found to be liable in some of these cases, it poses a huge challenge for arts organizations eager to jump in to the NFT scene. For now, we wait to see who the courts hold accountable. 

Sources:

LII / Legal Information Institute. “17 U.S. Code § 117 – Limitations on Exclusive Rights: Computer Programs.” Accessed May 1, 2022. https://www.law.cornell.edu/uscode/text/17/117.

Christie’s. “Appendix A: New York Conditions of Sale.” Christie’s. Accessed April 13, 2022. https://www.christies.com/media-library/pdf/conditions-of-sale/new-york-conditions-of-sale.pdf.

Crow, Kelly. “NFT Art the Latest Target for Online Fraudsters.” Financial News London, August 26, 2021. https://www.fnlondon.com/articles/nft-art-the-latest-target-for-fraudsters-20210826.

Cointelegraph. “Crypto DAO Spends €2.66M on Jodorowsky’s Dune Thinking They Would Own Its Copyright, Receives Mass Ridicule on Twitter.” Accessed April 19, 2022. https://cointelegraph.com/news/crypto-dao-spends-2-66m-on-jodorowsky-s-dune-thinking-they-would-own-its-copyright-receives-mass-ridicule-on-twitter.

“DeviantArt Protect: 80,000 NFT Alerts Sent by Team on DeviantArt.” Accessed April 20, 2022. https://www.deviantart.com/team/journal/DeviantArt-Protect-80-000-NFT-Alerts-Sent-902819882.

Fisher, Katya. “Once Upon a Time in NFT: Blockchain, Copyright, and the Right of First Sale Doctrine.” Cardozo Arts & Entertainment Law Journal 37, no. 3 (2019): 629-.

Goldstein, Caroline. “Model Emily Ratajkowski Blasted Richard Prince for Stealing Her Image. Now, She’s Taking It Back—and Selling It as an NFT.” Artnet News, April 23, 2021. https://news.artnet.com/market/emily-ratajkowski-nft-christies-1961581.

Graves, Franklin. “Sorry, Your NFT Is Worthless: The Copyright and Generative Art Problem for NFT Collections.” IPWatchdog.com | Patents & Patent Law, February 20, 2022. https://www.ipwatchdog.com/2022/02/20/sorry-nft-worthless-copyright-generative-art-problem-nft-collections/id=146163/.

Hale, Christine E, and Courtney Rogers Perrin. “NFT Lawsuits 2022 Roundup.” Lexology (blog). Mondaq Ltd, 2022. https://www.lexology.com/library/detail.aspx?g=1ce96c95-b567-4230-bbd5c71f0ac3c0d3#:~:text=In%20November%202021%2C%20production%20company,his%20handwritten%20Pulp%20Fiction%20script.

Kastrenakes, Jacob. “How Many Layers of Copyright Infringement Are in Emily Ratajkowski’s New NFT?” The Verge, April 24, 2021. https://www.theverge.com/2021/4/24/22399790/emily-ratajkowski-nft-christies-copyright-nightmare-richard-prince.

Kwan, Jacklin. “An Artist Died. Then Thieves Made NFTs of Her Work.” WIRED UK, July 28, 2021. https://www.wired.co.uk/article/nft-fraud-qinni-art.

Mackenzie, Simon, and Diana Berzina. “NFTs: Digital Things and Their Criminal Lives.” Crime, Media, Culture, August 19, 2021. https://journals.sagepub.com/doi/full/10.1177/17416590211039797.

Mattei, Shanti Escalante-De. “Christie’s NFT Auction with OpenSea Concludes with Middling $3.6 M. Result.” ARTnews.Com (blog), December 8, 2021. https://www.artnews.com/art-news/market/christies-opensea-nft-sale-1234612759/.

The NFTtorney. “New Digital World, Old Legal Rules,” January 31, 2022. https://nfttorney.com/2022/01/31/new-digital-world-old-legal-rules/.

The NFTtorney. “OpenSea Just Saved Their Users Millions in Potential Copyright Damages,” July 15, 2021. https://nfttorney.com/2021/07/15/opensea-just-saved-their-users-millions-in-potential-copyright-damages/.

“Richard Prince.” Accessed May 1, 2022. http://www.richardprince.com/.

Rizzo, Jessica. “The ‘Dune’ NFT Copyright Fiasco Is the Least of Crypto’s Legal Worries.” Wired. Accessed April 22, 2022. https://www.wired.com/story/nft-cryptocurrency-art-regulation-law/.

Schmalfeld, Jonathan. “Copyright Violations Could Crash the NFT Party.” Fortune, August 4, 2021. https://fortune.com/2021/08/04/nfts-copyright-violations-penalties-non-fungible-tokens-collectibles-nfttorney-jonathan-schmalfeld/.

Tiwari, Anirudh. “‘Wave of Litigation’ to Hit NFT Space as Copyright Issues Abound.” Cointelegraph, February 7, 2022. https://cointelegraph.com/news/wave-of-litigation-to-hit-nft-space-as-copyright-issues-abound.

Los Angeles Times. “This Picture of Emily Ratajkowski Is Free to Look at. But Its NFT Sold for $140,000.” May 17, 2021. https://www.latimes.com/entertainment-arts/story/2021-05-17/emily-ratajkowski-nft-sells-for-140000.

We understand writing as a form of art that comes directly from soul to page, an intimate reveal of human emotion.

This core concept of writing is complicated with the development of AI trained to write and write creatively. It is, of course, “thinking” about the act of writing while writing, and doesn’t really have the capacity to think about what it is writing in Flusser’s sense. 

AI writing models present a challenge to our notions of writing, but they may also be an overlooked tool to writers themselves. What do they mean for writers and the craft in the future? Could a robot write a New York Times Bestseller? 

A friend of mine recently reached out to me and asked if I would be willing to contribute a poem to a zine they were making with digital artists. They told me to write anything under the thematic umbrella of “Fluidity”. I wrote a very unstructured poem about my past and present constantly flowing into one another. Later, I was playing around with a Writing AI app called Inferkit, and I decided to see whether it would pick up on the idea of fluidity and motion if I fed it some lines of my poem. I gave it the first and last line of each stanza, and let it fill in the middle. The result: Not only did it capture the theme of “fluidity”, but it used a few choice words that I had used and did not feed it. To my surprise, it also picked up a level of plot and incorporated an entire last stanza involving turning into something else–eerily similar to my original. I was curious: Does this speak to my lack of originality as a writer, or is it a testament to the growing sophistication of Natural Language Processing and other AI writing mechanics? 

Natural Language Processing, GPT-3, & Its Uses:

Human language is not an easy thing to teach a machine. We have tone variances, we are able to understand that “she” is someone specific and variable, we understand that “bear” is an animal and “London” is a place. We also understand the feelings that accompany the words we choose. These are some of the challenges AI confronts when learning natural language. Most AI that has learned to write, speak, or communicate in any human language is built on what’s called Natural Language Processing. Natural Language Processing (NLP) is the utilization of vast amounts of language material, organized and structured for the AI to understand, to try and train artificial intelligence to speak or write in an organic, natural way. It is what informs chatbots, Google Maps, Google Translate, Siri, and Speech-to-text. Most of us interact with NLP systems in some way every day. 

One NLP AI system is GPT-3. GPT-3 was developed by Open AI, and is the latest and more sophisticated model used by a variety of platforms. Its learning comes from all corners of the internet, so it is trained on anything from novels, to blog posts, to ads, to Facebook comments. It is sophisticated enough to write entire news articles that are mostly indistinguishable from human writing. The eerie video of two robots talking with each other about what it means to be human is also GPT-3. Many of the creative writing AI apps are powered by this, and the sophistication of GPT-3’s language knowledge is what allows users to customize the tone, add characters, and build a story conjointly with the AI. The wide implementation of GPT-3 doesn’t come without its criticism. Controversies have arisen surrounding its use of racially inflammatory language outputs likely learned from biases on the internet, and also for its environmental impact. 

Xiaoice

Another Natural Language Processing model, perhaps the most famous one, is Microsoft’s Xiaoice. First developed in 2014, Xiaoice has become a celebrity, poet, news personality, and highly personal chatbot. Extremely popular in China, she has long-standing relationships with many of her users. Built on an “empathic computing framework”, Xiaoice is especially good at having real, emotional conversations with her users, creating a network of millions of fans. Xiaoice’s poetry was circulating online before anyone knew that AI had written it, and she wrote the first AI-authored published book of poetry, “The Sunlight and the Lost Glass Window”. Naturally, many poets disapproved of the work and felt it may mark the beginning of the desolation of the art form altogether. They contend that a machine that has never been alive could never capture human emotion poetically. Xiaoice’s intimate relationships with her users might attest otherwise. 

Comparison of a few AI Writing (Free) Programs

To learn a bit more about how the free creative writing apps generate content, I decided to test out a few. I primarily wanted to see their ability to pick up on style, tone, and plot. The main tools I used were Inferkit and Sudowrite. I did play around with some others, like Sassbook and Ryter which is primarily configured to help write articles and could not pick up on poetry format.

Examples
I fed Sudowrite the first four lines of the Mary Oliver poem, “Wild Geese”,  and let it do its thing. Here is the comparison between Sudowrite and the actual poem. The purple text notes where my typing ends and Sudowrite’s additions begin.

Sudowrite repeated the “Soft animal of your body” quite a bit, but it did pick up on the poem’s general theme of finding joy and acceptance in life. 

Here are the results of the same poem input using Inferkit.

Inferkit seemed to prefer shorter lines, and auto-generated the next words of the actual poem, “Tell me about your despair.” 

As I tried out these platforms with various writings other than my own, I noticed that if a work was particularly popular (and likely appearing on the internet more often), the AI already knows the next few lines. Both Sudowrite and Inferkit gave me the exact next paragraph when I was using Harry Potter and the Sorcerer’s Stone. 

Here is an example of Sudowrite given an excerpt from Octavia Butler’s Parable of the Sower.

In this example, Sudowrite picked up on the idea of injustice that runs through the novel, as well as the main character’s feelings towards it.  

Here is Inferkit with the same excerpt:

It seems in this example that Inferkit is writing this as a news piece or blog article about a current event, rather than a story plotline. These examples are specifically surrounding free applications of AIs automated writing. With access to GPT3 and coding skills, of course, the outputs would be different. I use these examples just to demonstrate the capabilities and shortcomings of these applications and the types of outputs they provide.

Implications in the Craft of Writing

The implications of more sophisticated NLP AI programs like GPT-3 entering the creative writing field are varied. AI Impact’s 2016 Expert Survey on Progress in AI asked about predictions of AI’s progress in the future surrounding specific tasks. For the task “write a New York Times Bestseller”, researchers estimated a 25% likelihood of it occurring in the next 20 years and a 62.5% likelihood within the next 50 years. This is around the same time frame they gave to “surgeon”, and is a significantly lower probability than the task “retail salesperson”.

We often center our conversations about creativity and AI around whether or not it can become “human enough” to replace us or to solve human problems without us. One writer called AI-generated writing “A deepfake of meaning itself.” What if instead of suffering over the thought of Barnes and Nobles being full of robot books, we thought about AI as an implement to enhance our art?

The relationship between humans, machines, and creative writing is not necessarily a new one. Alison Knowles created a poem called “House of Dust” using an IBM computer programming system called FORTRAN in 1967, and used one of the stanzas as inspiration for a large-scale sculpture. K Allado-McDowell co-wrote the novel Pharmako AI with GPT-3 in 2020. In both of these instances, artist and machine were in collaboration with the transformative nature of unpredictability provided by the AI. A study that asked writers to co-write with a “machine-in-the-loop” setup, meaning the AI plays a supporting role to the person’s inputs, found that those who wrote with the machine were more satisfied with the end result than those that wrote it without. 

AI may have the capability to profoundly affect the way we think about the act of writing moreso than the livelihood and paychecks of creative writers themselves. Of course, disruption of the creative traditions of a practice can provoke quite a bit of resistance (take Jackson Pollock’s early criticism, for example). 

Creative writing has long been a uniquely solitary act, the most substantial collaboration being with inspirations from past writers. We think of writers on retreat in a cabin in the woods, isolated while perfecting their craft. The idea of solitude as a necessity for becoming “self-forgetful” in order to achieve elevated creativity is, in many ways, something AI can give to a writer. 

Allado-Macdowell said on his process writing Pharmako AI, “At the end of the process, I felt more like I’d been divining, spelunking, or channeling than writing in a traditional sense.” Partnerships between writer and AI can generate serendipitous moments of creative gesture that allow a writer to break through writer’s block, and create unforeseen plots and descriptions.  It can also push the writer outside their own imagination and lived experiences, just as that isolation can distort their sense of self. 

Other Implications

Plagiarism Issues

The implications of more sophisticated NLP AI programs like GPT-3 entering the creative writing field are varied. With writers using AI as a collaborative tool, a critical potential issue is plagiarism. This topic has mostly been discussed through the lens of academic integrity, but there are parallel issues within creative writing. As mentioned earlier, inputting Harry Potter excerpts prompted word-for-word outputs from the book. A writer using platforms such as these could unintentionally be using full lines of writing by someone else.

And using a model that is trained on millions of pieces of writing, it may be difficult to discern what is random and what might be pulled from another source. In the cases of writers like Allado-Macdowell and Knowles, they were actually coding and training the machines, and more able to control the funnel of information that was going in and coming out. Those who don’t have the technological skills to train the machine themselves may opt to use programs like Inferkit and Sudowrite, where dangerous potentials could arise. 

“There are no laws for the novel. There never have been, nor can there ever be.”

Doris Lessing

AI might just change the laws of the novel. For now, a fully independent AI-written novel likely won’t be on the NYT bestseller list anytime soon. But maybe it’s time to consider letting AI into the practice. 

References:

AI Impacts. “2016 Expert Survey on Progress in AI,” December 14, 2016. https://aiimpacts.org/2016-expert-survey-on-progress-in-ai/.
The Guardian. “A Robot Wrote This Entire Article. Are You Scared yet, Human?,” September 8, 2020, sec. Opinion. https://www.theguardian.com/commentisfree/2020/sep/08/robot-wrote-this-article-gpt-3.
Clark, Elizabeth, Anne Spencer Ross, Chenhao Tan, Yangfeng Ji, and Noah A. Smith. “Creative Writing with a Machine in the Loop: Case Studies on Slogans and Stories.” In 23rd International Conference on Intelligent User Interfaces, 329–40. Tokyo Japan: ACM, 2018. https://doi.org/10.1145/3172944.3172983.
“Demo – InferKit.” Accessed February 14, 2022. https://app.inferkit.com/demo.
People’s Dialy Online. “First AI-Authored Collection of Poems Published in China – People’s Daily Online,” May 31, 2017. http://en.people.cn/n3/2017/0531/c90000-9222463.html.
Flusser, Vilém. “The Gesture of Writing.” In Gestures, 208. University of Minnesota Press, 2017.
Hoel, Eric. “I Got an Artificial Intelligence to Write My Novel.” Electric Literature (blog), June 10, 2021. https://electricliterature.com/i-got-an-artificial-intelligence-to-write-my-novel/.
Plagiarism Today. “How AI Will Change Authorship and Plagiarism,” February 12, 2019. https://www.plagiarismtoday.com/2019/02/12/how-ai-will-change-plagiarism/.
Literary Hub. “How Collaborating With Artificial Intelligence Could Help Writers of the Future,” November 9, 2021. https://lithub.com/how-collaborating-with-artificial-intelligence-could-help-writers-of-the-future/.
IBM Cloud Education. “What Is Natural Language Processing? | IBM,” July 2, 2020. https://www.ibm.com/cloud/learn/natural-language-processing.
“Jackson Pollock Criticism Rebuted by Helen Harrison – The New York Times.” Accessed March 3, 2022. https://www.nytimes.com/2010/12/05/nyregion/05spotli.html.
Kantosalo, Anna, and Sirpa Riihiaho. “Quantifying Co-Creative Writing Experiences.” Digital Creativity 30, no. 1 (January 2, 2019): 23–38. https://doi.org/10.1080/14626268.2019.1575243.
Loutfi, Amira. “12 Artificial Intelligence Tools to Write Your Novel For You.” MetaStellar (blog), October 18, 2021. https://www.metastellar.com/2021/10/18/12-artificial-intelligence-tools-to-write-your-novel-for-you/.
“Next Chapter in Artificial Writing.” Nature Machine Intelligence 2, no. 8 (2020): 419–419. https://doi.org/10.1038/s42256-020-0223-0.
OpenAI. “OpenAI.” Accessed February 28, 2022. https://openai.com/.
Rogers, Hannah Star. “Cheering Artificial Intelligence Leader: Creative Writing and Materializing Design Fiction.” Leonardo 53, no. 1 (n.d.): 58.
Rytr. “Rytr · Best AI Writer, Content Generator & Writing Assistant.” Rytr. Accessed February 24, 2022. https://rytr.me.
“Sassbook AI Writer: High-Quality AI Text Generator.” Accessed February 24, 2022. https://sassbook.com/ai-writer.
Schmelzer, Ronald. “What Is GPT-3? Everything You Need to Know.” SearchEnterpriseAI. Accessed February 22, 2022. https://www.techtarget.com/searchenterpriseai/definition/GPT-3.
Spencer, Geoff. “Much More than a Chatbot: China’s Xiaoice Mixes AI with Emotions and Wins over Millions of Fans.” Microsoft Stories Asia, November 1, 2018. https://news.microsoft.com/apac/features/much-more-than-a-chatbot-chinas-xiaoice-mixes-ai-with-emotions-and-wins-over-millions-of-fans/.
TWiT Tech Podcast Network. Microsoft’s Xiaoice Bot Is Getting Smarter, 2018. https://www.youtube.com/watch?v=P8tEB0W9YnM.
Weller, Chris. “Chinese Poetry Scholars Are ‘disgusted’ by a New Book Written by a Robot.” Business Insider. Accessed February 28, 2022. https://www.businessinsider.com/chinese-poetry-written-by-robot-2017-6.
“Why Writers Need Solitude. Writing Takes Extraordinary Persistence… | by Jan Fortune | Medium.” Accessed March 3, 2022. https://janfortune.medium.com/why-writers-need-solitude-f5e9bd93b17a.
Wilk, Elvia. “What AI Can Teach Us About the Myth of Human Genius.” The Atlantic, March 28, 2021. https://www.theatlantic.com/culture/archive/2021/03/pharmako-ai-possibilities-machine-creativity/618435/.
Tech2. “XiaoIce Is the AI Chatbot That Millions of Lonely Chinese Are Turning to for Comfort- Technology News, Firstpost,” 13:53:37 +05:30. https://www.firstpost.com/tech/news-analysis/xiaoice-is-the-ai-chatbot-that-millions-of-lonely-chinese-are-turning-to-for-comfort-9910921.html.

If an organization is, for lack of a better term, a technology Luddite, in orther words not using technologies available and paid for at their most effective — blaming the technology, not investing in training, and avoiding anything “new,” technology expenditures are a cost not an opportunity. To create a digitally-openminded (but not easily duped) institution, training and research in the space need to be part of the Corporate Culture. Something most often lead from the top, but also something that takes time to change (usually 1 – 3 years).

As organization’s assemble technology infrastructure, a mind to operations AND engagement must be front and center. Public wifi needs to be firewalled from operational tech. Investments must be maintained with planning, as ‘falling behind’ in the tech space opens up significant security and privacy leakage — and in its worst moments, complete loss of data.

And, just because something is “in” doesn’t mean it is “right” or “right for you.” For example, pushing EVERYTHING to the cloud creates a significant security issues, especially if things are “free” (nothing in tech is free).

So, how does one USE technology efficiently and effectively to ENACT mission by ENGAGING stakeholders? It is likely much more complicated than anyone ever wants to think about.

As we go into our first Module (Artificial Intelligence) our adventure begins. Your Hands-On for this module is to create a chatbot (you can look at the hands on tab and we’ll walk through in class). As you discovered in your Ted Talk — AI isn’t new (it’s 60 years old!) BUT it is reaching new opportunities and, particularly, engaging at a business and consumer level previously unheard of. Additionally — AI has significant ethical issues. (at least in its current state). Be sure to consider the intended and unintended consequences of all technology as we move through our adventures this semester.

The 2nd module transitions from AI to our interactives with our audiences (externally and internally). Our 3rd Module will focus on Blockchain and, you too, will create an NFT. We will wrap up the class with a more sensitive discussion of infrastructure, security, and privacy (with a touch of big tech throughout).

I have your feedback from the survey and will review that and how we will progress through our May 10th final exam period / Rabbit Hole #2 presentations.

On Monday night we will be diving into Technology Infrastructure of our industries (and many of the considerations an arts manager must keep in mind). 
In addition, please consider your experience as an intern / professional and the frameworks the company had in place for employee technology. We will discuss during class.

We will also do our 3rd and final required Hands On share out (assuming most people didn’t go deep into coding and did either the IFTTT, Zapier or Scratch).  If you did any of the last 3 I would hope the Hands On would take less than the outer limit of 2 hours to complete, and maybe it was/is either fun or informative!

See you tomorrow.

Other laws exist that provide access rights / protection to the internet / from bad actors (see Sam Houle’s work and CCPR on AMT Lab).

In fact, the recent discussion in the US as to whether Broadband (access to high speed internet) is an infrastructure issue is quite pertinent.

We will focus on conversation on public policy, individual and corporate security (data hacks ). See you soon!

Each group will rotate through presentations in order listed on the group list at the end of the email below. When it is your turn to present — you have a MAX of 5 minutes (you will be given a 1 minute warning and stopped at 5). Then the group has 2 minutes to make prompted comments in your box note to give you feedback. Then the next person will start. If you only present for 3 minutes — that’s fine. (in concept the prompt for the presentation as detailed in the assignment could result in a 3 minute share out). That will allow for some conversation about Weekly News at the end.

You are welcome to arrive early or remain in one of the rooms to listen to more presentations (just don’t comment in the box note).

I am emailing this notification as well as posting to Slack and announcements. Please DM in Slack with any questions.

Group A – 6:30
Devyn
Ryan
JD
Emily
Carol

Group B – 6:30
Madison
Liz
Mina
Yuxin
Snow
Lauren

Group C – 7:10
Cameron
Emmy
Angela
Junyu
Ariel
Youssef

Group D – 7:10
Katelyn
Isaiah
Shun-Sho
Helen
Sandra

Group E – 7:50
Rachel
Andrew
Xiaocheng
Suraj
Alexandra

Group F – 7:50
Amy
Caro
Dillon
Hanmo
Katie
Rishi

Then we will do our Hot Weekly News share out

Then embark on investigation /  discussion about our industries and the technologies needed to meet the demands of our new normal.

We will be using BOX NOTES and everyone will be speaking at some point during class.

Enjoy your short readings and weekly news.