Category: Big Data

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.

Colorado artist used artificial intelligence program Midjourney to win first place

When Jason Allen submitted his “Théâtre D’opéra Spatial” into the Colorado State Fair’s fine arts competition last week, the sumptuous print was an immediate hit. It also marked a new milestone in the growth of artificial intelligence.

There has been a lot of comment about how a Colorado artist used artificial intelligence program Midjourney to win first place. This is seen as historic, but, as is pointed out in the Washington Post piece, people weren’t sure photography is an art. You could say that in both cases the art is in selection, not the image making that is taken over by a machine.

I can’t help thinking that an important part of art is the making. When I make art things they are amateurish and wouldn’t win any prizes, but I enjoy the making and improving at making. Having played with Midjourney it does have some of the pleasures of creating, but now the creation is through iteratively trying different combinations of words.

The New York Times has story about the win too, An A.I.-Generated Picture Won an Art Prize. Artists Aren’t Happy.

Vol. 31 No. 1 (2022): Ethics in the Age of Smart Systems: Special Issue | The International Review of Information Ethics

The Special Issue of the International Review of Information Ethics has just been fully put up at Vol. 31 No. 1 (2022): Ethics in the Age of Smart Systems: Special Issue. In addition to co-editing it, I co-authored an Editorial commenting On Dialogue and Artificial Intelligence that deals with the LaMDA as sentience issue.

This special issue came out a series of dialogues that AI4Society organized with our partners. These were followed by a symposium on “Ethics in the Age of Smart Machine.”

Workplace Productivity: Are You Being Tracked?

“We’re in this era of measurement but we don’t know what we should be measuring,” said Ryan Fuller, former vice president for workplace intelligence at Microsoft.

The New York Times has essay on  Workplace Productivity: Are You Being Tracked? The neat thing is that the article tracks your reading of it to give you a taste of the sorts of tracking now being deployed for remote (and on site) workers. If you pause and don’t scroll it puts up messages like “Hey are you still there? You’ve been inactive for 32 seconds.”

But Ms. Kraemer, like many of her colleagues, found that WorkSmart upended ideas she had taken for granted: that she would have more freedom in her home than at an office; that her M.B.A. and experience had earned her more say over her time.

What is new is the shift to remote work due to Covid. Many companies are fine with remote work if they can guarantee productivity. The other thing that is changing is the use of tracking for not just manual work, but also for white-collar work.

I’ve noticed that this goes hand in hand with self-tracking. My Apple Watch/iPhone offer a weekly summary of my browsing. It also offers to track my physical activity. If I go for a walk, somewhere close to a kilometer it asks if I want this tracked as exercise.

The questions raised by the authors of the New York Time article include Whether we are tracking the right things? What are we losing with all this tracking? What is happening to all this data? Can companies sell the data about employees?

The article is by Jodi Kantor and Arya Sundaram. It is produced by Aliza Aufrichtig and Rumsey Taylor. Aug. 14, 2022

Zampolli Prize Awarded to Voyant Tools

Spyral Notebook Detail (showing code cell and stacked graphs)

Yesterday I gave the triennial Zampolli Prize lecture that honoured Voyant. The lecture is given at the annual ADHO Digital Humanities conference which this year is being hosted by the University of Tokyo. The award notice is here Zampolli Prize Awarded to Voyant Tools. Some of the things I touched on in the talk included:

  • The genius of of Stéfan Sinclair who passed in August 2020. Voyant was his vision from the time of his dissertation for which he develop HyperPo.
  • The global team of people involved in Voyant including many graduate research assistants at the U of Alberta. See the About page of Voyant.
  • How Voyant built on ideas Stéfan and I developed in Hermeneutica about collaborative research as opposed to the inherited solitary paradigm.
  • How we have now developed an extension to Voyant called Spyral. Spyral is a notebook programming environment built on JavaScript. It allows you to document your Voyant explorations, save parameters for corpora and tools, preprocess texts, postprocess results, and create new visualizations. It is, in short, a full data analysis and visualization environment built into Voyant so you can easily call up and explore results in Voyant’s already rich tool set.
  • In the image above you can see a Spyral code cell that outputs two stacked graphs where the same pattern of words is graphed over two different, but synchronized, corpora. You can thus compare the use of the pattern over time between the two datasets.
  • Replication as a practice for recovering an understanding of innovative technologies now taken for granted like tokenization or the KWIC. I talked about how Stéfan and I have been replicating important text processing technologies as a way of understanding the history of computing and the digital humanities. Spyral was the environment we developed for documenting our replications.
  • I then backed up and talked about the epistemological questions about knowledge and knowledge things in the digital age that grew out of and then inspired our experiments in replication. These go back to attempts to think-through tools as knowledge things that bear knowledge in ways that discourse doesn’t. In this context I talked about the DIKW pyramid (data, information, knowledge, wisdom) that captures current views about the relationships between data and knowledge.
  • Finally I called for help to maintain and extend Voyant/Spyral. I announced the creation of a consortium to bring us together to sustain Voyant.

It was an honour to be able to give the Zampolli lecture on behalf of all the people who have made Voyant such a useful tool.

Lessons from the Robodebt debacle

How to avoid algorithmic decision-making mistakes: lessons from the Robodebt debacle

The University of Queensland has a research alliance looking at Trust, Ethics and Governance and one of the teams has recently published an interesting summary of How to avoid algorithmic decision-making mistakes: lessons from the Robodebt debacle. This is based on an open paper Algorithmic decision-making and system destructiveness: A case of automatic debt recovery. The web summary article is a good discussion of the Australian 2016 robodebt scandal where an unsupervised algorithm issued nasty debt collection letters to a large number of welfare recipients without adequate testing, accountability, or oversight. It is a classic case of a simplistic and poorly tested algorithm being rushed into service and having dramatic consequences (470,000 incorrectly issued debt notices). There is, as the article points out, also a political angle.

UQ’s experts argue that the government decision-makers responsible for rolling out the program exhibited tunnel vision. They framed welfare non-compliance as a major societal problem and saw welfare recipients as suspects of intentional fraud. Balancing the budget by cracking down on the alleged fraud had been one of the ruling party’s central campaign promises.

As such, there was a strong focus on meeting financial targets with little concern over the main mission of the welfare agency and potentially detrimental effects on individual citizens. This tunnel vision resulted in politicians’ and Centrelink management’s inability or unwillingness to critically evaluate and foresee the program’s impact, despite warnings. And there were warnings.

What I find even more disturbing is a point they make about how the system shifted the responsibility for establishing the existence of the debt from the government agency to the individual. The system essentially made speculative determinations and then issued bills. It was up to the individual to figure out whether or not they had really been overpaid or there was a miscalculation. Imagine if the police used predictive algorithms to fine people for possible speeding infractions who then had to prove they were innocent or pay the fine.

One can see the attractiveness of such a “fine first then ask” approach. It reduces government costs by shifting the onerous task of establishing the facts to the citizen. There is a good chance that many who were incorrectly billed will pay anyway as they are intimidated and don’t have the resources to contest the fine.

It should be noted that this was not the case of an AI gone bad. It was, from what I have read, a fairly simple system.

Street View Privacy

How do you feel about people being able to look at your house in Google Street View? Popular Science has an article by David Nield, on “How to hide your house on every map app: Stop people from peering at your place” (May 18, 2022).

This raises questions about where privacy starts and a right to look or know stops. Can I not walk down a street and look at the faces of houses? Why then should I not be able to look at the face on Street View and other similar technologies? What about the satellite view? Do people have the right to see into my back yard from above?

This is a similar issue, though less fraught, as face databases. What rights do I have to my face? How would those rights connect to laws about Name, Image and Likeness (NIL) (or rights of publicity) which became an issue recently in amateur sports in the US. As for Canada, Rights of Publicity are complex and vary from province to province, but there is generally a recognition that:

  • People should have the right “to control the commercial use of name, image, likeness and other unequivocal aspects of one’s identity (eg, the distinct sound of someone’s voice).” (See Lexology article)
  • At the same time there is recognition that NIL can be used to provide legitimate information to the public.

Returning to the blurring of your house facade in Street View; I’m guessing the main reason the companies provide this is for security for people in sensitive positions or people being stalked.

Health agency tracked Canadians’ trips to liquor store via phones during pandemic

The report reveals PHAC was able to view a detailed snapshot of people’s behaviour, including grocery store visits, gatherings with family and friends, time…

The National Post is reporting about the Public Health Agency of Canada and their use of mobility data that a group of us wrote about in The Conversation (Canada). The story goes into more detail about how Health agency tracked Canadians’ trips to liquor store via phones during pandemic. The government provided one of the reports commissioned by PHAC from BlueDot to the House of Commons. The Ethics Committee report discussing what happened and making recommendations is here.