I discovered the Artificial Intelligence Incident Database developed by the Partnership on AI. The Database contains reports on things that have gone wrong with AIs like the Australian Centerlink robodebt debacle.
The Incident Database was developed to help educate developers and encourage learning from mistakes. They have posted a paper to arXiv on Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database.
Ask Delphi is an intriguing AI that you can use to ponder ethical questions. You type in a situation and it will tell you if it is morally acceptable or not. It is apparently built not on Reddit data, but on crowdsourced data, so it shouldn’t be as easy to provoke into giving toxic answers.
In their paper, Delphi: Towards Machine Ethics and Norms they say that they have created a Commonsense Norm Bank, “a collection of 1.7M ethical judgments on diverse real-life situations.” This contributes to Delphi’s sound pronouncements, but it doesn’t seem available for others yet.
AI Weirdness has a nice story on how she fooled Delphi.
Public can try pulling faces to trick the technology, while critics highlight human rights concerns
From the Guardian story, Scientists create online games to show risks of AI emotion recognition, I discovered Emojify, a web site with some games to show how problematic emotion detection is. Researchers are worried by the booming business of emotion detection with artificial intelligence. For example, it is being used in education in China. See the CNN story about how In Hong Kong, this AI reads children’s emotions as they learn.
A Hong Kong company has developed facial expression-reading AI that monitors students’ emotions as they study. With many children currently learning from home, they say the technology could make the virtual classroom even better than the real thing.
With cameras all over, this should worry us. We are not only be identified by face recognition, but now they want to know our inner emotions too. What sort of theory of emotions licenses these systems?
Using Danish witchcraft folklore as a model, the researchers from UCLA and Berkeley analysed thousands of social media posts with an artificial intelligence tool and extracted the key people, things and relationships.
The Guardian has a nice story on Why people believe Covid conspiracy theories: could folklore hold the answer? This reports on research using folklore theory and artificial intelligence to understand conspiracies.
The story maps how Bill Gates connects the coronavirus with 5G for conspiracy fans. They use folklore theory to understand the way conspiracies work.
Folklore isn’t just a model for the AI. Tangherlini, whose specialism is Danish folklore, is interested in how conspiratorial witchcraft folklore took hold in the 16th and 17th centuries and what lessons it has for today.
Whereas in the past, witches were accused of using herbs to create potions that caused miscarriages, today we see stories that Gates is using coronavirus vaccinations to sterilise people. …
The research also hints at a way of breaking through conspiracy theory logic, offering a glimmer of hope as increasing numbers of people get drawn in.
The story then addresses the question of what difference the research might make. What good would a folklore map of a conspiracy theory do? The challenge of research is the more information clearly doesn’t work in a world of information overload.
The paper the story is based on is Conspiracy in the time of corona: automatic detection of emerging Covid-19 conspiracy theories in social media and the news, by Shadi Shahsavari, Pavan Holur, Tianyi Wang , Timothy R Tangherlini and Vwani Roychowdhury.
Apparently Non-Fungible Tokens (NFTs) of game models are not going down well with fans according to a story, Dead By Daylight fans unhappy Hellraiser model is an NFT.
Even thought Behaviour isn’t selling the NFTs themselves, they are facilitating the sale of them by providing the models from the game. Gaming fans seem to view blockchain and NFTs as dubious and environmentally unsound technology. Behaviour’s response was,
We hear and understand the concerns you raised over NFTs. Absolutely zero blockchain tech exists in Dead by Daylight. Nor will it ever. Behaviour Interactive does not sell NFTs.
On a related note, Valve is banning blockchain and NFT games.
All 50,000+ of Trump’s tweets, instantly searchable
Thanks to Kaylin I found the Trump Twitter Archive: TTA – Search. Its a really nice clean site that lets you search or filter Trump’s tweets from when he was elected to when his account was shut down on January 8th, 2021. You can also download the data if you want to try other tools.
I find reading his tweets now to be quite entertaining. Here are two back to back tweets that seems to almost contradict each other. First he boasts about the delivery of vaccines, and then talks about Covid as Fake News!
Jan 3rd 2021 – 8:14:10 AM EST: The number of cases and deaths of the China Virus is far exaggerated in the United States because of @CDCgov’s ridiculous method of determination compared to other countries, many of whom report, purposely, very inaccurately and low. “When in doubt, call it Covid.” Fake News!
Jan 3rd 2021 – 8:05:34 AM EST: The vaccines are being delivered to the states by the Federal Government far faster than they can be administered!
Apple unveiled new software Thursday that scans photos and messages on iPhones for child pornography and explicit messages sent to minors in a major new effort to prevent sexual predators from using Apple’s services.
The Washington Post and other news venues are reporting that Apple will scan iPhones for child pornography. As the subtitle to the article puts it “Apple is prying into iPhones to find sexual predators, but privacy activists worry governments could weaponize the feature.” Child porn is the go-to case when organizations want to defend surveillance.
The software will scan without our knowledge or consent which raises privacy issues. What are the chances of false positives? What if the tool is adapted to catch other types of images? Edward Snowden and the EFF have criticized this move. It seems inconsistent with Apple’s firm position on privacy and refusal to even unlock
It strikes me that there is a great case study here.
The US military is testing AI that helps predict events days in advance, helping it make proactive decisions..
Endgadget has a story on how the Pentagon believes its precognitive AI can predict events ‘days in advance’. It is clear that for most the value in AI and surveillance is prediction and yet there are some fundamental contradictions. As Hume pointed out centuries ago, all prediction is based on extrapolation from past behaviour. We simply don’t know the future; the best we can do is select features of past behaviour that seemed to do a good job predicting (retrospectively) and hope they will work in the future. Alas, we get seduced by the effectiveness of retrospective work. As Smith and Cordes put it in The Phantom Pattern Problem:
How, in this modern era of big data and powerful computers, can experts be so foolish? Ironically, big data and powerful computers are part of the problem. We have all been bred to be fooled—to be attracted to shiny patterns and glittery correlations. (p. 11)
What if machine learning and big data were really best suited for suited for studying the past and not predicting the future? Would there be the hype? the investment?
When the next AI winter comes we in the humanities could pick up the pieces and use these techniques to try to explain the past, but I’m getting ahead of myself and predicting another winter.
IBM’s artificial intelligence was supposed to transform industries and generate riches for the company. Neither has panned out. Now, IBM has settled on a humbler vision for Watson.
The New York Times has a story about What Ever Happened to IBM’s Watson? The story is a warning to all of us about the danger of extrapolating from intelligence behaviour in one limited domain to others. Watson got good enough at trivia question answering (or posing) to win at Jeopardy!, but that didn’t scale out.
IBM’s strategy is interesting to me. Developing an AI to win at a game like Jeopardy! was what IBM did with Deep Blue that won at chess in 1997. Winning at a game considered paradigmatically a game of intelligence is a great way to get public relations attention.
Interestingly what seems to be working with Watson is not the moon shot game playing type of service, but the automation of basic natural language processing tasks.
Having recently read Edwin Black’s IBM and the Holocaust: The Strategic Alliance Between Nazi Germany and America’s Most Powerful Corporation I must say that the choice of the name “Watson” grates. Thomas Watson was responsible for IBM’s ongoing engagement with the Nazi’s for which he got a medal from Hitler in 1937. Watson didn’t seem to care how IBM’s data processing technology was being used to manage people especially Jews. I hope the CEOs of AI companies today are more ethical.
Leonardo Impett has a nice demonstration here of ImageGraph: a visual programming language for the Visual Digital Humanities. ImageGraph is a visual programming environment that works with Google Colab. When you have your visual program you can compile it into Python in a Colab notebook and then run that notebook. The visual program is stored in your Github account and the Python code can, of course, be used in larger projects.
The visual programming language has a number of functions for handling images and using artificial intelligence techniques on them. It also has text functions, but they are apparently not fully worked out.
I love the way Impett combines off the shelf systems while adding a nice visual development environment. Very clean.
