Category: Big Data

2023 Annual Public Lecture in Philosophy

Last week I gave the 2023 Annual Public Lecture in Philosophy. You can Watch a Recording here. The talk was on The Eliza Effect: Data Ethics for Machine Learning.

I started the talk with the case of Kevin Roose’s interaction with Sydney (Microsoft’s name for Bing Chat) where it ended up telling Roose that it loved him. From there I discussed some of the reasons we should be concerned with the latest generation of chatbots. I then looked at the ethics of LAION-5B as an example of how we can audit the ethics of projects. I ended with some reflections on what an ethics of AI could be.

Pause Giant AI Experiments: An Open Letter

We call on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.

The Future of Life Institute is calling on AI labs to pause with a letter signed by over 1000 people (including myself), Pause Giant AI Experiments: An Open Letter – Future of Life Institute. The letter asks for a pause so that safety protocols can be developed,

AI labs and independent experts should use this pause to jointly develop and implement a set of shared safety protocols for advanced AI design and development that are rigorously audited and overseen by independent outside experts. These protocols should ensure that systems adhering to them are safe beyond a reasonable doubt.

This letter to AI labs follows a number of essays and opinions that maybe we are going too fast and should show restraint. This in the face of the explosive interest in large language models after ChatGPT.

  • Gary Marcus wrote an essay in his substack on “AI risk ≠ AGI risk” arguing that just because we don’t have AGI doesn’t mean there isn’t risk associated with the Mediocre AI systems we do have.
  • Yuval Noah Harari has an opinion in the New York Times with the title, “You Can Have the Blue Pill or the Red Pill, and We’re Out of Blue Pills” where he talks about the dangers of AIs manipulating culture.

We have summoned an alien intelligence. We don’t know much about it, except that it is extremely powerful and offers us bedazzling gifts but could also hack the foundations of our civilization. We call upon world leaders to respond to this moment at the level of challenge it presents. The first step is to buy time to upgrade our 19th-century institutions for a post-A.I. world and to learn to master A.I. before it masters us.

It is worth wondering whether the letter will have an effect, and if it doesn’t, why we can’t collectively slow down and safely explore AI.

ChatGPT: Chatbots can help us rediscover the rich history of dialogue

The rise of AI chatbots provides an opportunity to expand the ways we do philosophy and research, and how we engage in intellectual discourse.

I published an article in The Conversation today on, ChatGPT: Chatbots can help us rediscover the rich history of dialogue. This touches on a topic that I’ve been thinking about a lot … how chatbots are dialogue machines and how we can draw on the long history of dialogue in philosophy to understand the limits/potential of chatbots like ChatGPT.

 

ChatGPT listed as author on research papers: many scientists disapprove

The editors-in-chief of Nature and Science told Nature’s news team that ChatGPT doesn’t meet the standard for authorship. “An attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs,” says Magdalena Skipper, editor-in-chief of Nature in London. Authors using LLMs in any way while developing a paper should document their use in the methods or acknowledgements sections, if appropriate, she says.

We are beginning to see interesting ethical issues crop up regarding the new LLMs (Large Language Models) like ChatGPT. For example, Nature has an news article, ChatGPT listed as author on research papers: many scientists disapprove,.

It makes sense to document use, but why would we document use of ChatGPT and not, for example, use of a library or of a research tool like Google Scholar? What about the use of ChatGPT demands that it be acknowledged?

Fuck the Poetry Police: On the Index of Major Literary Prizes in the United States

The LARB has a nice essay by Dan Sinykin on how researchers have used data to track how poetry prizes are distributed unequally titled, Fuck the Poetry Police: On the Index of Major Literary Prizes in the United States. The essay talks about the creation of the Post45 Data Collective which provides peer review for post-1945 cultural datasets.

Sinykin talks about this as an “act as groundbreaking as the research itself” which seems a bit of an exaggeration. It is important that data is being reviewed and published, but it has been happening for a while in other fields. Nonetheless, this is a welcome initiative, especially if it gets attention like the LARB article. In 2013 the Tri-Council (of research agencies in Canada) called for a culture of research data stewardship. In 2015 I worked with Sonja Sapach and Catherine Middleton on a report on a Data Management Plan Recommendation for Social Science and Humanities Funding Agencies. This looks more at the front end of requiring plans from people submitting grant proposals that are asking for funding for data-driven projects, but this was so that data could be made available for future research.

Sinykin’s essay looks at the poetry publishing culture in the US and how white it is. He shows how data can be used to study inequalities. We also need to ask about the privilege of English poetry and that of culture from the Global North. Not to mention research and research infrastructure.

Why scientists are building AI avatars of the dead | WIRED Middle East

Advances in AI and humanoid robotics have brought us to the threshold of a new kind of capability: creating lifelike digital renditions of the deceased.

Wired Magazine has a nice article about Why scientists are building AI avatars of the dead. The article talks about digital twin technology designed to create an avatar of a particular person that could serve as a family companion. You could have your grandfather modelled so that you could talk to him and hear his stories after he has passed.

The article also talks about the importance of the body and ideas about modelling personas with bodies. Imagine wearing motion trackers and other sensors so that your bodily presence could be modelled. Then imagine your digital twin being instantiated in a robot.

Needless to say we aren’t anywhere close yet. See this spoof video of the robot Sophia on a date with Will Smith. There are nonetheless issues about the legalities and ethics of creating bots based on people. What if one didn’t have permission from the original? Is it ethical to create a bot modelled on a historical person? a living person?

We routinely animate other people in novels, dialogue (of the dead), and in conversation. Is impersonating someone so wrong? Should people be able to control their name and likeness under all circumstances?

Then there are the possibilities for the manipulation of a digital twin or through such a twin.

As for the issue of data breaches, digital resurrection opens up a whole new can of worms. “You may share all of your feelings, your intimate details,” Hickok says. “So there’s the prospect of malicious intent—if I had access to your bot and was able to talk to you through it, I could change your attitude about things or nudge you toward certain actions, say things your loved one never would have said.”

 

How AI image generators work, like DALL-E, Lensa and stable diffusion

Use our simulator to learn how AI generates images from “noise.”

The Washington Post has a nice explainer on how text to image generators work: How AI image generators work, like DALL-E, Lensa and stable diffusion. They let you play with the generator, though you have to stick with the predefined phrases. What I hadn’t realized was the role of static noise in the diffusion model. Not sure how it works, but it seems to train the AI to recognize and then generate in noisy images.

Character.AI: Dialogue on AI Ethics

Part of image generated from text, “cartoon pencil drawing of ethics professor and student talking” by Midjourney, Oct. 5, 2022.

Last week I created a character on Character.AI, a new artificial tool created by some ex-Google engineers who worked on LaMDA, the language model from Google that I blogged about before.

Character.AI, which is now down for maintenance due to all the users, lets you quickly create a character and then enter into dialogue with it. It actually works quite well. I created “The Ethics Professor” and then wrote a script of questions that I used to engage the AI character. The dialogue is below.

Pages: Page 1, Page 2

Issues around AI text to art generators

A new art-generating AI system called Stable Diffusion can create convincing deepfakes, including of celebrities.

TechCrunch has a nice discussion of Deepfakes for all: Uncensored AI art model prompts ethics questions. The relatively sudden availability of AI text to art generators has provoked discussion on the ethics of creation and of large machine learning models. Here are some interesting links:

It is worth identifying some of the potential issues:

  • These art generating AIs may have violated copyright in scraping millions of images. Could artists whose work has been exploited sue for compensation?
  • The AIs are black boxes that are hard to query. You can’t tell if copyrighted images were used.
  • These AIs could change the economics of illustration. People who used to commission and pay for custom art for things like magazines, book covers, and posters, could start just using these AIs to save money. Just as Flickr changed the economics of photography, MidJourney could put commercial illustrators out of work.
  • We could see a lot more “original” art in situations where before people could not afford it. Perhaps poster stores could offer to generate a custom image for you and print it. Get your portrait done as a cyberpunk astronaut.
  • The AIs could reinforce visual bias in our visual literacy. Systems that always see Philosophers as old white guys with beards could limit our imagination of what could be.
  • These could be used to create pornographic deepfakes with people’s faces on them or other toxic imagery.

EU Artificial Intelligence Act

With the introduction of the Artificial Intelligence Act, the European Union aims to create a legal framework for AI to promote trust and excellence. The AI Act would establish a risk-based framework to regulate AI applications, products and services. The rule of thumb: the higher the risk, the stricter the rule. But the proposal also raises important questions about fundamental rights and whether to simply prohibit certain AI applications, such as social scoring and mass surveillance, as UNESCO has recently urged in the Recommendation on AI Ethics, endorsed by 193 countries. Because of the significance of the proposed EU Act and the CAIDP’s goal to protect fundamental rights, democratic institutions and the rule of law, we have created this informational page to provide easy access to EU institutional documents, the relevant work of CAIDP and others, and to chart the important milestones as the proposal moves forward. We welcome your suggestions for additions. Please email us.

The Center for AI and Digital Policy (CAIDP) has a good page on the EU Artificial Intelligence Act with links to different resources. I’m trying to understand this Act the network of documents related to it, as the AI Act could have a profound impact on how AI is regulated, so I’ve put together some starting points.

First, the point about the potential influence of the AI Act is made in a slide by Giuliano Borter, a CAIDP Fellow. The slide deck is a great starting point that covers key points to know.

Key Point #1 – EU Shapes Global Digital Policy

• Unlike OECD AI Principles, EU AI legislation will have legal force with consequences for businesses and consumers

• EU has enormous influence on global digital policy (e.g. GDPR)

• EU AI regulation could have similar impact

Borter goes on to point out that the Proposal is based on a “risk-based approach” where the higher the risk the more (strict) regulation. This approach is supposed to provide legal room for innovative businesses not working on risky projects while controlling problematic (riskier) uses. Borter’s slides suggest that an unresolved issue is mass surveillance. I can imagine that there is the danger that data collected or inferred by smaller (or less risky) services is aggregated into something with a different level of risk. There are also issues around biometrics (from face recognition on) and AI weapons that might not be covered.

The Act is at the moment only a proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) – the Proposal was launched in April of 2021 and all sorts of entities, including the CAIDP are suggesting amendments.

What was the reason for this AI Act? In the Reasons and Objective opening to the Proposal they write that “The proposal is based on EU values and fundamental rights and aims to give people and other users the confidence to embrace AI-based solutions, while encouraging businesses to develop them.” (p. 1) You can see the balancing of values, trust and business.

But I think it is really the economic/business side of the issue that is driving the Act. This can be seen in the Explanatory Statement at the end of the Report on artificial intelligence in a digital age (PDF) from the European Parliament Special Committee on Artificial Intelligence in a Digital Age (AIDA).

Within the global competition, the EU has already fallen behind. Significant parts of AI innovation and even more the commercialisation of AI technologies take place outside of Europe. We neither take the lead in development, research or investment in AI. If we do not set clear standards for the human-centred approach to AI that is based on our core European ethical standards and democratic values, they will be determined elsewhere. The consequences of falling further behind do not only threaten our economic prosperity but also lead to an application of AI that threatens our security, including surveillance, disinformation and social scoring. In fact, to be a global power means to be a leader in AI. (p. 61)

The AI Act may be seen as way to catch up. AIDA makes the supporting case that “Instead of focusing on threats, a human-centric approach to AI based on our values will use AI for its benefits and give us the competitive edge to frame AI regulation on the global stage.” (p. 61) The idea seems to be that a values based proposal that enables regulated responsible AI will not only avoid risky uses, but create the legal space to encourage low-risk innovation. In particular I sense that there is a linkage to the Green Deal – ie. that AI is being a promising technology that could help reduce energy use through smart systems.

Access Now also has a page on the AI Act. They have a nice clear set of amendments that show where some of the weaknesses in the AI Act could be.