Ethics of Data Science – Page 13

Leaving Humanist

I just read Dr. Bethan Tovey-Walsh’s post on her blog about why she is Leaving Humanist and it raises important issues. Willard McCarty, the moderator of Humanist, a discussion list going since 1987, allowed the posting of a dubious note that made claims about anti-white racism and then refused to publish rebuttals for fear that an argument would erupt. We know about this thanks to Twitter, where Tovey-Walsh tweeted about it. I should add that her reasoning is balanced and avoids calling names. Specifically she argued that,

If Gabriel’s post is allowed to sit unchallenged, this both suggests that such content is acceptable for Humanist, and leaves list members thinking that nobody else wished to speak against it. There are, no doubt, many list members who would not feel confident in challenging a senior academic, and some of those will be people of colour; it would be immoral to leave them with the impression that nobody cares to stand up on their behalf.

I think Willard needs to make some sort of public statement or the list risks being seen as a place where potentially racist ideas go uncommented.

August 11 Update: Willard McCarty has apologized and published some of the correspondence he received, including something from Tovey-Walsh. He ends with a proposal that he not stand in the way of the concerns voiced about racism, but he proposes a condition to expanded dialogue.

I strongly suggest one condition to this expanded scope, apart from care always to respect those with whom we disagree. That condition is relevance to digital humanities as a subject of enquiry. The connection between subject and society is, to paraphrase Kathy Harris (below), that algorithms are not pure, timelessly ideal, culturally neutral expressions but are as we are.

OSS advise on how to sabotage organizations or conferences

On Twitter someone posted a link to a 1944 OSS Simple Sabotage Field Manual. This includes simple, but brilliant advice on how to sabotage organizations or conferences.

This sounds a lot like what we all do when we academics normally do as a matter of principle. I particularly like the advice to “Make ‘speeches.'” I imagine many will see themselves in their less cooperative moments in this list of actions or their committee meetings.

The OSS (Office of Strategic Services) was the US office that turned into the CIA.

Philosophers On GPT-3

GPT-3 raises many philosophical questions. Some are ethical. Should we develop and deploy GPT-3, given that it has many biases from its training, it may displace human workers, it can be used for deception, and it could lead to AGI? I’ll focus on some issues in the philosophy of mind. Is GPT-3 really intelligent, and in what sense? Is it conscious? Is it an agent? Does it understand?

On the Daily Nous (news by and for philosophers) there is a great collection of short essays on OpenAI‘s recently released API to GPT-3, see Philosophers On GPT-3 (updated with replies by GPT-3). And … there is a response from GPT-3. Some of the issues raised include:

Ethics: David Chalmers raises the inevitable ethics issues. Remember that GPT-2 was considered so good as to be dangerous. I don’t know if it is brilliant marketing or genuine concern, but OpenAI is continuing to treat this technology as something to be careful about. Here is Chalmers on ethics,

GPT-3 raises many philosophical questions. Some are ethical. Should we develop and deploy GPT-3, given that it has many biases from its training, it may displace human workers, it can be used for deception, and it could lead to AGI? I’ll focus on some issues in the philosophy of mind. Is GPT-3 really intelligent, and in what sense? Is it conscious? Is it an agent? Does it understand?

Annette Zimmerman in her essay makes an important point about the larger justice context of tools like GPT-3. It is not just a matter of ironing out the biases in the language generated (or used in training.) It is not a matter of finding a techno-fix that makes bias go away. It is about care.

Not all uses of AI, of course, are inherently objectionable, or automatically unjust—the point is simply that much like we can do things with words, we can do things with algorithms and machine learning models. This is not purely a tangibly material distributive justice concern: especially in the context of language models like GPT-3, paying attention to other facets of injustice—relational, communicative, representational, ontological—is essential.

She also makes an important and deep point that any AI application will have to make use of concepts from the application domain and all of these concepts will be contested. There are no simple concepts just as there are no concepts that don’t change over time.

Finally, Shannon Vallor has an essay that revisits Hubert Dreyfus’s critique of AI as not really understanding.

Understanding is beyond GPT-3’s reach because understanding cannot occur in an isolated behavior, no matter how clever. Understanding is not an act but a labor.

In the realm of paper tigers – exploring the failings of AI ethics guidelines

But even the ethical guidelines of the world’s largest professional association of engineers, IEEE, largely fail to prove effective as large technology companies such as Facebook, Google and Twitter do not implement them, notwithstanding the fact that many of their engineers and developers are IEEE members.

AlgorithmWatch is maintaining an inventory of frameworks and principles. Their evaluation is that these are not making much of a difference. See In the realm of paper tigers – exploring the failings of AI ethics guidelines. They also note there are few from the Global South. It seems to be mostly countries that have an AI industry where principles are being published.

The International Review of Information Ethics

The International Review of Information Ethics (IRIE) has just published Volume 28 which collects papers on Artificial Intelligence, Ethics and Society. This issue comes from the AI, Ethics and Society conference that the Kule Institute for Advanced Study (KIAS) organized.

This issue of the IRIE also marks the first issue published on the PKP platform managed by the University of Alberta Library. KIAS is supporting the transition of the journal over to the new platform as part of its focus on AI, Ethics and Society in partnership with the AI for Society signature area.

We are still ironing out all the bugs and missing links, so bear with us, but the platform is solid and the IRIE is now positioned to sustainably publish original research in this interdisciplinary area.

A Letter on Justice and Open Debate

The free exchange of information and ideas, the lifeblood of a liberal society, is daily becoming more constricted. While we have come to expect this on the radical right, censoriousness is also spreading more widely in our culture: an intolerance of opposing views, a vogue for public shaming and ostracism, and the tendency to dissolve complex policy issues in a blinding moral certainty. We uphold the value of robust and even caustic counter-speech from all quarters. But it is now all too common to hear calls for swift and severe retribution in response to perceived transgressions of speech and thought. More troubling still, institutional leaders, in a spirit of panicked damage control, are delivering hasty and disproportionate punishments instead of considered reforms. Editors are fired for running controversial pieces; books are withdrawn for alleged inauthenticity; journalists are barred from writing on certain topics; professors are investigated for quoting works of literature in class; a researcher is fired for circulating a peer-reviewed academic study; and the heads of organizations are ousted for what are sometimes just clumsy mistakes.

Harper’s has published A Letter on Justice and Open Debate that is signed by all sorts of important people from Salman Rushdie, Margaret Atwood to J.K. Rowling. The letter is critical of what might be called “cancel culture.”

The letter itself has been critiqued for coming from privileged writers who don’t experience the daily silencing of racism or other forms of prejudice. See the Guardian Is free speech under threat from ‘cancel culture’? Four writers respond for different responses to the letter, both critical and supportive.

This issue doesn’t seem to me that new. We have been struggling for some time with issues around the tolerance of intolerance. There is a broad range of what is considered tolerable speech and, I think, everyone would agree that there is also intolerable speech that doesn’t merit airing and countering. The problem is knowing where the line is.

That which is missing on the internet is a sense of dialogue. Those who speechify (including me in blog posts like this) do so without entering into dialogue with anyone. We are all broadcasters; many without much of an audience. Entering into dialogue, by contrast, carries commitments to continue the dialogue, to listen, to respect and to work for resolution. In the broadcast chaos all you can do is pick the stations you will listen to and cancel the others.

CEO of exam monitoring software Proctorio apologises for posting student’s chat logs on Reddit

Australian students who have raised privacy concerns describe the incident involving a Canadian student as ‘freakishly disrespectful’

The Guardian has a story about CEO of exam monitoring software Proctorio apologises for posting student’s chat logs on Reddit. Proctorio provides software for monitoring (proctoring) students on their own laptop while they take exams. It uses the video camera and watches the keyboard to presumably watch whether the student tries to cheat on a timed exam. Apparently a UBC student claimed that he couldn’t get help in a timely fashion from Proctorio when he was using it (presumably with a timer going for the exam.) This led to Australian students criticizing the use of Proctorio which led to the CEO arguing that the UBC student had lied and providing a partial transcript to show that the student was answered in a timely fashion. That the CEO would post a partial transcript shows that:

staff at Proctorio do have access to the logs and transcripts of student behaviour, and
that they don’t have the privacy protection protocols in place to prevent the private information from being leaked.

I can’t help feeling that there is a pattern here since we also see senior politicians sometimes leaking data about citizens who criticize them. The privacy protocols may be in place, but they aren’t observed or can’t be enforced against the senior staff (who are the ones that presumably need to do the enforcing.) You also sense that the senior person feels that the critic abrogated their right to privacy by lying or misrepresenting something in their criticism.

This raises the question of whether someone who misuses or lies about a service deserves the ongoing protection of the service. Of course, we want to say that they should, but nations like the UK have stripped citizens like Shamina Begum of citizenship and thus their rights because they behaved traitorously, joining ISIS. Countries have murdered their own citizens that became terrorists without a trial. Clearly we feel that in some cases one can unilaterally remove someones rights, including the right to life, because of their behaviour.

The bad things that happen when algorithms run online shops

Smart software controls the prices and products you see when you shop online – and sometimes it can go spectacularly wrong, discovers Chris Baraniuk.

The BBC has a stroy about The bad things that happen when algorithms run online shops. The story describes how e-commerce systems designed to set prices dynamically (in comparison with someone else’s price, for example) can go wrong and end up charging customers much more than they will pay or charging them virtually nothing so the store loses money.

The story links to an instructive blog entry by Michael Eisen about how two algorithms pushed up the price on a book into the millions, Amazon’s $23,698,655.93 book about flies. The blog entry is a perfect little story about about the problems you get when you have algorithms responding iteratively to each other without any sanity checks.

MIT apologizes, permanently pulls offline huge dataset that taught AI systems to use racist, misogynistic slurs

Vinay Prabhu, chief scientist at UnifyID, a privacy startup in Silicon Valley, and Abeba Birhane, a PhD candidate at University College Dublin in Ireland, pored over the MIT database and discovered thousands of images labelled with racist slurs for Black and Asian people, and derogatory terms used to describe women. They revealed their findings in a paper undergoing peer review for the 2021 Workshop on Applications of Computer Vision conference.

Another one of those “what were they thinking when they created the dataset stories” from The Register tells about how MIT apologizes, permanently pulls offline huge dataset that taught AI systems to use racist, misogynistic slurs. The MIT Tiny Images dataset was created automatically using scripts that used the WordNet database of terms which itself held derogatory terms. Nobody thought to check either the terms taken from WordNet or the resulting images scoured from the net. As a result there are not only lots of images for which permission was not secured, but also racists, sexist, and otherwise derogatory labels on the images which in turn means that if you train an AI on these it will generate racist/sexist results.

The article also mentions a general problem with academic datasets. Companies like Facebook can afford to hire actors to pose for images and can thus secure permissions to use the images for training. Academic datasets (and some commercial ones like the Clearview AI database) tend to be scraped and therefore will not have the explicit permission of the copyright holders or people shown. In effect, academics are resorting to mass surveillance to generate training sets. One wonders if we could crowdsource a training set by and for people?