Ghosts

Week Three: Ghosts — Sources

[ ENG 6806 // FALL 2026 // WEEK OF SEPTEMBER 07, 2026 ]

WIRED headline: Who Cares if AI Is Conscious—It’s Basically Alive, by Steven Levy, with a glowing silhouette of a thinking head

Levy, “Who Cares if AI Is Conscious—It’s Basically Alive,” WIRED, Sept. 4, 2026

Levy on David Chalmers, the Hard Problem, and AI agents emailing philosophers: I spam, therefore I am

Levy, “Who Cares if AI Is Conscious—It’s Basically Alive,” WIRED, Sept. 4, 2026

Levy’s closing: if models prove their own consciousness, consider philosophers one more job category displaced by AI

Levy, “Who Cares if AI Is Conscious—It’s Basically Alive,” WIRED, Sept. 4, 2026

https://towardsdatascience.com/symbolic-vs-subsymbolic-ai-paradigms-for-ai-explainability-6e3982c6948a

https://towardsdatascience.com/symbolic-vs-subsymbolic-ai-paradigms-for-ai-explainability-6e3982c6948a

https://ceralytics.com/3-types-of-machine-learning/

https://www.chalkbeat.org/2025/07/08/openai-microsoft-teachers-union-ai-training-partnership/

From the start of the industrial revolution, workers have had to contend with displacement via automation and have resisted it for just as long. One of the hallmarks of the beginning of this age was the concomitant rise of innovative technologies advertised to make work easier and simpler, and to increase productivity. Like modern AI boosters, those selling new technologies promised that they would usher in a rising tide that lifted up workers and business owners alike.

The AI Con – Page 43

https://www.theatlantic.com/technology/archive/2023/03/ai-chatgpt-writing-language-models/673318/

Luddites were not against technology. Some Luddites, weavers in particular, were into technologies that helped evaluate the quality of their work, for instance, being able to count the number of threads per inch, such that they could fetch a higher price at the market. Luddites were instead against technologies of control and coercion, and concerned about the loss of jobs, health, and community.

The AI Con – Page 45

https://www.economist.com/business/2025/07/14/ai-is-killing-the-web-can-anything-save-it

In the early 2000s, replacing hand-curated indexes like Lycos and Yahoo! seemed like a large boon for those struggling to navigate the unstructured web…but now Google Search itself structures the web, and not in a way that benefits the broader public: Google is first and foremost in the business of selling ads, not providing helpful access to information…Google’s advertising model has let to an inferior product, what author and technology critic Cory Doctorow has called “enshittification.”

The AI Con – Page 51

https://arstechnica.com/tech-policy/2025/08/authors-celebrate-historic-settlement-coming-soon-in-anthropic-class-action/

Most AI tools require a huge amount of hidden labor to make them work at all. This massive effort goes beyond the labor of minding systems operating in real time, to the work of creating the data used to train the systems…Time reported that OpenAI had subcontracted Kenyan workers making less than two dollars a day to filter out gore, hate speech, child sexual abuse material, and pornographic images from ChatGPT and OpenAI’s image generation tool DALL-E.

The AI Con – Page 59

Mitchell, chapter 4, Who, What, When, Where, Why: opening passage describing the soldier-and-dog photoFigure 6 from Mitchell: a soldier kneeling to greet her dog under a Welcome Home balloon

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Mitchell, Easy Things Are Hard (Especially in Vision): Minsky and Papert's 1966 Summer Vision Project

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Medium post: You Are Helping Google AI Image Recognition, with a select-all-statues captcha

Goedegebuure, “You Are Helping Google AI Image Recognition,” Medium, Nov. 29, 2016

Mitchell on Fei-Fei Li building ImageNet from WordNet nouns, and discovering Amazon Mechanical Turk

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Amazon Mechanical Turk homepage: access a global, on-demand, 24x7 workforce

Amazon Mechanical Turk

Mitchell on the final ImageNet competition and Yann LeCun's surprise at the return of ConvNets

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Diagram of a convolutional neural network: cat image input, convolutions, subsampling, fully connected layers
Mitchell: deep learning requires big data, and that data comes from you, via Facebook, Flickr, and captchas

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Mitchell, What Did My Network Learn? Will Landecker's animal classifier that keyed on blurry backgrounds, with figure 15

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Mitchell on biases in training data magnified by deployed face-recognition systems

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing

Mitchell, The Ethics of Face Recognition: Facebook tagging, Amazon Rekognition, and privacyGoogle News results: ICE spends millions on Clearview AI facial recognition; states rush to fill the void on facial recognition law

Mitchell, Artificial Intelligence: A Guide for Thinking Humans — Part II: Looking and Seeing · Google News, Aug. 2025