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I recently stumbled upon a post of ArsTechnica reporting a sort of update about legal proceedings related to generative AI and fair-use. Or, better, a follow up on a number of these proceedings by a very relevant plaintiff: Getty Images. I linked some relevant posts about Getty in a post about the AI act. In a nutshell, however, Getty has sued Stability AI because:
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I live in Italy, and one of the stylized facts (or stereotypes, which is probably a potentially reasonable synonym) about Italians is that we love pizza, we play the mandolin, and that we love football. Well, I guess that the mandolin truly is an unjustified stereotype, but football is actually pretty popular. It’s a constant source of conversation and often sparks passionate debates. It is probably the same for other countries as well, but it is the inception for this small reflection.
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I haven’t been commenting news about the recent events about Generative AI developments and exploitation by the industry, the political scenario for over one month, and in Donal Trump 2.0 era it is quite a long time. Some recent news pushed me to get back to this topic: it’s nothing really new, and honestly this could be a full-time job, but it’s really worth reminding, here and there. Moreover, it seems that some warnings that might have looked like old time marxist positions forcefully brought forward in time, back to the present, to cite Robert Zemekis, are instead to be taken very seriously and not disregarded as they have been so far.
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If you read this blog you have already encountered a reference to a book titled The Enigma of Reason, by Hugo Mercier and Dan Sperber. It took me some time to read it, probably due to the complexity of the matter, the depth of the discussion, that is based on scientific researches by the authors, and the distance between my background (Computer Science) and the discipline in which this work is set (Cognitive Science).
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In my last post I wrote that I was noticing a growing resentment about AI in general, although specifically the target is generally represented by commercial initiatives based on LLMs. Their ways of operating would make proud Mark Zuckerberg and his motto “move fast and break things”… and of course, Meta is clearly part of this game as well.
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I think some readers have started to feel a hint of sickness when they hear about LLMs. This includes new developments—not just in research, but across the entire socio-economic-technical system—along with emerging and existing limits, unsolved issues with training data, legal challenges, and discussions about their real capabilities and what they might bring about. Probably, a significant share of people sharing this feeling were already involved in computer science or ICT technologies before LLMs, whereas younger people are more curious and generally have more positive feelings about LLMs and news related to them. I am stumbling more and more frequently on comments that show even resentment about LLMs, acrimony, maybe symptom of envy of the attention they have, and potential they are showing.
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Throughout my career, I have focused on studying collective behaviors and complex systems, aiming to define computational models that replicate overarching (emerging?) aggregated dynamic properties for explanation or prediction.
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Some days ago I read a post about bias written by a colleague here at the Department of Informatics, Systems and Communication of the University of Milano-Bicocca. The post discussed the relationship between what he called “model bias” and “domain bias”. The point was, in some cases the bias is not in the model, or - better - it was not introduced by the model, but it is rather replicated from the data describing a phenomenon. In turn, those data are not necessarily biased, what is biased is our world (the domain), our society, sometimes even our formal rules.
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The landscape of Italian journalism is quite depressing, from my point of view. I mostly listen to an independent local radio channel (Radio Popolare - by the way, they anticipated crowdfunding with a subscription mechanism although this subscription does not imply that they produce contents accessible only to subscribers, a curious and interesting approach) and read Internazionale, a magazine collecting and translating in Italian articles from International journals from all over the world. The last number of Internazionale proposed the translation in Italian of this article titled “AI Is a False God - The real threat with super intelligence is falling prey to the hype”, by Navneet Alang, from The Walrus, another editorial initiative that is worth following.
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If you have already read some of the posts in this blog you know my position on bibliometric forms of research evaluation. I promise this time I will be brief, but it’s a tasty bit, from my point of view.
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Some bits and pieces that you can interpolate, and that - in my opinion - are part of a trajectory that you might see as well.
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In an earlier post I started talking about bibliometrics, some of its flaws, and what I think has become one of the facets of an ideology, something Jerry Z. Muller called “The tyranny of metrics”. I’m going to add two ways to enlarge your H-index that, at the same time, also represent a totally legitimate action in the overall context of a line research.
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You might know that I’m the coordinator of a master’s degree, in Italy. Ennio Flaiano, an Italian screenwriter, playwright, novelist, journalist, author of numerous enlightening aphorisms, said that:
In Italy the shortest line between two points is the arabesque
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Some time ago, I made a post on contributing to the Internet public good game. I want to follow up with a couple curious trajectories of photos I took and shared on Pixabay.
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The so-called AI Act has been agreed upon by the EU Parliament and member states. The news is about the formal agreement among these not necessarily aligned actors, more than the content of the regulation, which still needs to be adopted by the Parliament and Council to be become EU law. Contents were in fact mostly defined beforehand, although some details, such as exceptions to the regulations for national security, specific crimes, and military/defense systems were defined in the last negotiation.
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I think that a very relevant recent news passed us by with little attention by the academic sector. It’s definitely worth reminding it to myself and to the few readers of my blog.
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I don’t think I can really add something to the debate on research assessment. But maybe I can do something useful, at least to those that did not follow thoroughly the subject. I can provide a summary with some selected readings.
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A few weeks ago I wrote a post about participating the public goods game of the academia by reviewing papers. That’s important, and in a sense irrespectively of the quality of the review.
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I immediately admit that I have a preference for small scale events.
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A recent preprint captured my attention, and very likely this is due to the fact that it confirms and provides a systematic quantitative support to a personal notion. I directly use author’s words without filters:
“Total articles indexed in Scopus and Web of Science have grown exponentially in recent years; in 2022 the article total was 47% higher than in 2016, which has outpaced the limited growth, if any, in the number of practising scientists. Thus, publication workload per scientist (writing, reviewing, editing) has increased dramatically. We define this problem as the strain on scientific publishing.” - The strain on scientific publishing. Mark A. Hanson, Pablo Gómez Barreiro, Paolo Crosetto, Dan Brockington
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The higher education system, and the mainstream shared conception is that high levels of specialization are desirable, and useful at the individual level. If we project this kind of idea as the most shared principle driving individual training from high-school, to university, and potentially grad-school, we end up with a population of specialists. I’ve read a book on the advantages of being a generalist (Range, by David Epstein) rather than having an early specialization, but surely one side effect of focusing intensely on something and not wasting time on other things is that we tend to become ignorant on any other subject outside our area of specialization.
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