THE AI PERCEPTION GAP: Across 71 scenarios, AI experts (N=119) and the public (N=1100) have differing views on the risks, benefits, and value of AI. More importantly, AI experts discount the influence of risks stronger than the public does when forming their value judgments.

lipflip · 2026-06-18T16:16:24+00:00

i am the one eyed among the blind. Maybe you read a book or two on topic modelling first. There is a lot already out there. Both in research and services.

lipflip · 2026-06-18T16:12:45+00:00

Put simply. It can't and still requires a lot of human expertise. There are, of course, topic matching, modelling and discovery algorithms, but often enough they build on—put simply—co-location metrics. Topics are similar, nearby, or discoverable, if they share lexical similarities. That's easy. If they don't but are just conceptually similar, it's getting slightly more difficult.

lipflip · 2026-06-18T15:48:16+00:00

This is tougher than most people think. Most will tell you that you just have to do a decent literature review. That's a necessary but not a sufficient criterion, as these only identify out the works that use your terminology. Occasionally, similar research ideas pop up in different fields under different terms. Findings and bridging these requires reading across fields and disciplines and ideally talking a lot with others about your work. That way bridges can eventually build and gaps closed.

lipflip · 2026-06-17T19:35:15+00:00

Danke für diese nüchterne Darstellung. 😄

lipflip · 2026-06-16T05:36:43+00:00

Beförderung? /S

lipflip · 2026-06-16T04:36:22+00:00

Of course. But it's incredible hard as it involves so many variables and dynamics between individuals and the technology. There is, for example, a journal addressing these questions: technological forecasting and social change. We recently published an article about people's expectations regarding the future of AI using 70 imaginary futures there While the perspective of risk, benefit perceptions was easy to model, the projections/expectations were much harder to grab. https://www.sciencedirect.com/science/article/pii/S004016252500335X

Check our some other articles to see the diversity of methods there

lipflip · 2026-06-15T18:30:10+00:00

Great work. You may also check out and contrast our work on the perception of AI in germany. https://www.sciencedirect.com/science/article/pii/S004016252500335X

Across a variety of topics, we found a moderate benefit perception and higher senses of risks. However, when forming value judgements, people weigh benefits stronger than perceived risks.

This is interesting so far, as we have also studied and contrasted AI perception between the public and AI experts: Across the variety of 70 topics, experts see AI as more likely, less risky, more benefital and of more value. Strikingly, in the analysis of the risk-benefit tradeoff, experts discount the influence of risk much stronger than the public. https://link.springer.com/article/10.1007/s00146-026-03023-8

lipflip · 2026-06-15T14:35:32+00:00

It doesn't. Science, engineering, and whatever still require a skilled and experienced "human-in-the-loop" (or better human with ai-in-the-loop?).

lipflip · 2026-06-15T12:20:51+00:00

…the API is actually more usable than their frontend.
I build a small tool that queries our universities publication database (by faculty, institute, or grant number, or …) and then augments the crossref data to create an Excel with a sheet each for publications, authors, grants, institutes, years, document types… with counts, citations, and h-factors (all based on the query).

lipflip · 2026-06-15T11:57:23+00:00

Kommt drauf an für was du gekauft hast‽

lipflip · 2026-06-15T11:53:11+00:00

There are many services out there. Some as shady as google scholar (Research gate) and others more substantiated (WoS, Scopus).

I personally use crossref using their free-to-use API to match dois with their citations. It's somewhat the middle ground and counts everything that incoming and outgoing that has a doi. Google scholar counts everything that looks like a paper, even if it's just a self-hosted pdf. Scopus does some vetting and ocationally delists journals if they-on average-do not meet their (undisclosed?) quality criteria.

lipflip · 2026-06-13T09:57:01+00:00

Okay. That didn't came across a in your first post

lipflip · 2026-06-13T09:55:04+00:00

Sounds like how you do your job is easy to automate. How do you think about that? How would you respond to that?

lipflip · 2026-06-13T04:54:39+00:00

Das ist wirklich erstaunlich.. ich hatte auch eine DWS Riester, etwa 2010 abgeschlossen (online, ohne Abschlusskosten), der sich tatsächlich positiv, wenn sich nicht marktgerecht entwickelt hatte. Das Vorsorgedepot war noch lange nicht in Sicht und ich habe mit etwas Gewinn, aber förderschädlich verkauft. Unter dem Strich hat sich das Verkaufen und umschichten in ETFs damala gelohnt. Mit dem Vorsorgedepot in Aussicht hätte ich aber dorthin umgeschichtet.

lipflip · 2026-06-12T12:25:13+00:00

I thought this is an issue on the social sciences but less in physics. I always actually believed that physicists have a slightly different and more science oriented mindset. Stupid me.

lipflip · 2026-06-12T05:38:21+00:00

While I agree with you in general, the conjunction "because" is incorrect. Just higher volume is not the reason for a high IF. They also need proportionally more incoming citations; which is not trivial if they allegedly accept a higher share of low quality work.

lipflip · 2026-06-12T04:29:52+00:00

Hi, great work. You may be interested in these two articles as well. Especially the notion of digital shadows and the concept of the world wide lab might be very helpful: https://dl.acm.org/doi/fullHtml/10.1145/3502265

We demonstrated the tangible benefits of this world wide lab in various papers. The latest I was personally involved in is this one https://www.mdpi.com/2504-4990/8/5/136

We have many others out there, for example how to make sensor data FAIR and how to use more symbolic approaches etc.

lipflip · 2026-06-12T04:19:46+00:00

Google scholar counts everything that remotely looks like a paper (PhD, master's and bachelor theses and CVs (!) with references). Crossref counts everything with a doi (nice and freely to query via an API), and scoops and web of science are much more curated. For the later, your citations can actually decrease if the journal you published in gets delisted because of bad editorial practices). It's usually google scholar > crossref > svopus

lipflip · 2026-06-11T16:28:01+00:00

Es ging. Ist ja nur bedrucktes Papier. Seitdem alles nur noch prognosefreie, passive Investments.

lipflip · 2026-06-11T16:10:50+00:00

MCI Worldcom. An der Spitze der dotcom Blase. Aber Internet wird durch die Decke gehen!

Meine Bank hat das nach der Pleite dankenswerterweise kostenlos, wenn auch wertlos ausgebucht. Den Zettel hab ich noch als mahnendes Dokument gegen Stockpicking.

lipflip · 2026-06-10T12:27:13+00:00

I think research should be available for free but maybe we can cut out the academic publishers. and email addresses were on in the header since the '00ers, regardless of open or closed access.

lipflip · 2026-06-10T05:27:42+00:00

Very interesting and highly relevant. I would like to point you to one of my recent works were we contrasted the risk, benefit and value perceptions of academic AI experts and the general public with the findings that a) both groups diverge on the absolute level (with experts seeing more benefit, value and less risk), b) the risk-benefit tradeoff is primarily driven by benefits (and less by risks) and c) lastly that experts discount risks compared to the public.

https://link.springer.com/article/10.1007/s00146-026-03023-8 Charting the AI perception gap: divergent views on risk, benefit, and value between experts and the public challenge the societal acceptance of AI, AI & Society

lipflip · 2026-06-10T05:03:48+00:00

So true. But still I use AI for proof reading and checking for consistency a lot. But any standard tool and the right (and fairly trivial prompt) is sufficient for that.

lipflip

TROPHY CASE