An interactive, illustrated timeline of historic moments in humankind’s quest for information. With annotations by Jeremy Norman.
History of Information is a searchable database of events in information. The link will show you the digital humanities category and what the creator thought were important events. I must say that it looks rather biased towards the interventions of white men.
Cycloramas are the virtual reality of the 19th century. Long paintings, sometimes with props, were mounted in the round in special buildings that allowed people to feel immersed in a painted space. These remind us of the variety of types of media that have surpassed – the forgotten types of media.
I remember the beginnings of computer-assisted presentations. My unit at the University of Toronto Computing Services experimented with the first tools and projectors. The three-gun projectors were finicky to set up and I felt a little guilty promoting set ups which I knew would take lots of technical support. In one presentation on digital presentations there was actually a colleague under the table making sure all the technology worked while I pitched it to faculty.
Alas, PowerPoint came to dominate though now we have a bunch of innovative presentation tools that work on the web from Google Sheets to Prezi.
Now back to Tufte. His critique still stands. Presentation tools have a cognitive style that encourages us to break complex ideas into chunks and then show one chunk at a time in a linear sequence. He points out that a well designed handout or pamphlet (like his pamphlet on The Cognitive Style of PowerPoint) can present a lot more information in a way that doesn’t hide the connections. You can have something more like a concept map that you take people through on a tour. Prezi deserves credit for paying attention to Tufte and breaking out of the linear style.
Now, of course, there are AI tools that can generate presentations like Presentations.ai or Slideoo. You can see a list of a number of them here. No need to know what you’re presenting, an AI will generate the content, design the slides, and soon present it too.
Nökkvi Jarl Bjarnason gave a talk on the emergence of national and regional game studies. What does it mean to study game culture in a country or region? How is locality appealed to in game media or games or other aspects of game culture?
Felania Liu presented on game preservation in China and the challenges her team faces including issues around the legitimacy of game studies.
Hirokazu Hamamura gave the final keynote on the evolution of game media starting with magazines and then shifting to the web.
I presented a paper co-written with Miki Okabe and Keiji Amano. We started with the demographic challenges faced by Japan as its population shrinks. We then looked at what Japanese Game Companies are doing to attract and support women and families. There is a work ethics that puts men and women in a bind where they are expected to work such long hours that there really isn’t any time left for “work-life balance.”
The conference was held in person at Nagoya Zokei University and brilliantly organized by Keiji Amano and Jean-Marc Pelletier. We limited online interventions to short lightning talks so there was good attendance.
Accuracy, fairness and speed are the guiding values for AP’s news report, and we believe the mindful use of artificial intelligence can serve these values and over time improve how we work.
AP also suggests they don’t see chatbots replacing journalists any time soon as the “the central role of the AP journalist – gathering, evaluating and ordering facts into news stories, video, photography and audio for our members and customers – will not change.”
It should be noted (as AP does) that they have an agreement with OpenAI.
A top concern for the Times is that ChatGPT is, in a sense, becoming a direct competitor with the paper by creating text that answers questions based on the original reporting and writing of the paper’s staff.
It remains to be seen what the legalities are. Does using a text in order to train a model constitute the making of a copy in violation of copyright? Does the model contain something equivalent to a copy of the original? These issues are being explored in the AI image generating space where Stability AI is being sued by Getty Images. I hope the New York Times doesn’t just settle quietly before there is a public airing of the issues around the exploitation/ownership of written work. I also note that the Author’s Guild is starting to advocate on behalf of authors,
“It says it’s not fair to use our stuff in your AI without permission or payment,” said Mary Rasenberger, CEO of The Author’s Guild. The non-profit writers’ advocacy organization created the letter, and sent it out to the AI companies on Monday. “So please start compensating us and talking to us.”
This could also have repercussions in academia as many of us scrape the web and social media when studying contemporary issues. For that matter what do we think about the use of our work? One could say that our work, supported as it is by the public, should be fair game from gathering, training and innovative reuse. Aren’t we supported for the public good? Perhaps we should assert that academic prose is available for training models?
The Office of the Data Protection Commissioner in Kenya first instructed Worldcoin to stop collecting personal data in May.
I don’t know what to think about Worldcoin. Is it one more crypto project doomed to disappear or could it be a nasty exploitive project designed to corner identity by starting starting in Kenya. Imagine having to get orbed just to use local government services online! Fortunately Kenya is now ordering them to stop their exploitation; see the TechCrunch story, Worldcoin ignored initial order to stop iris scans in Kenya, records show.
In sum, AI acting on its own cannot induce human extinction in any of the ways that extinctions have happened in the past. Appeals to the competitive nature of evolution or previous instances of a more intelligent species causing the extinction of a less intelligent species reflect a common mischaracterization of evolution by natural selection.
Could artificial intelligence (AI) soon get to the point where it could enslave us? An Amii colleague sent me to this sensible article, The Illusion Of AI’s Existential Riskthat argues that it is extremely unlikely that an AI could evolve to the point where it could manipulate us and prevent us from turning it off. One of the points they make is that the situation is completely different from past extinctions.
Our safety is the topic of Brian Christian’s excellent The Alignment Problem book which talks about different approaches to developing AIs so they are aligned with our values. An important point made by Stuart Russell and quoted in the book is that we don’t want AIs to have the same values as us, we want them to value our having values and to pay attention to our values.
This raises the question of how an AI might know what we value. One approach is Constitutional AI where we train ethical AIs on a constitution that captures our values and then use it to model others.
One of the problems, however, with ethics is that human ethics isn’t simple and may not be something one can capture in a constitution. For this reason another approach is Inverse Reinforcement Learning (IRL) where were ask an AI to infer our values from a mass of evidence of ethical discourse and behaviour.
My guess is that this is what they are trying at OpenAI in their Superalignment project. Imagine an ethical surveillance project that uses IRL to develop a (black) moral box which can be used to train AIs to be aligned. Imagine if it could be tuned to different community ethics?
The game itself is collection game where you roll a ever growing ball of things that you might see in a typical Japanese house. The balls will allow a prince to rebuild the stars accidentally destroyed by his father, King of All Cosmos. (The image above is of Takahashi as the King.) Rachael Hutchinson has a chapter in her book Japanese Culture Through Videogames about the game and Japan.
OpenAI has announced a Superalignment team and 4 year project to create an automated alignment researcher. They believe superintelligence (an AI more intelligent than humans) is possible within a decade and therefore we need to accelerate research into alignment. They believe developing an AI alignment researcher that is itself an AGI will give them a way to scale up and “iteratively align superintelligence.” In other words they want to set an AI to aligning more powerful AIs.
Alignment is an approach to AI safety that tries to develop AIs so they act as we would want and expect them to. The idea is to make sure that right out of the box AIs would behave in ways aligned with our values.
First, and importantly, OpenAI has to figure out how to align an AGI so that it can tun the superintelligences to come.
You can’t get superalignment without alignment, and we don’t really know what that is or how to get it. There isn’t consensus as to what our values should be so an alignment would have to be to some particular ethical position.
Why is OpenAI focusing only on superalignment? Why not try a number of the approaches from promoting regulation to developing more ethical training datasets? How can they be so sure about one approach? What do they know that we don’t? Or … what do they think they know?
Snoswell believes we should start by “acknowledging and addressing existing harms”. There are plenty of immediate difficult problems that should be addressed rather than “kicking the meta-ethical can one block down the road, and hoping we don’t trip over it later on.”
Technical safety isn’t a problem that can be solved. It is an ongoing process of testing and refining as this Tweet from Yann LeCunn puts it.
Anyway, I wish them well. No doubt interesting research will come out of this initiative which I hope OpenAI will share. In the meantime the rest of us can carry on with the boring safety research.