Sam Matla talks about the collector's fallacy in a negative light, and for many/most, he might be right. But for some, collecting examples and evidence of particular things is crucially important. The key is to have some idea of what you're collecting and why.

Historians collecting small facts over time may seem this way, but out of their collection can emerge patterns which otherwise would never have been seen.

cf: Keith Thomas article

concrete examples of this to show the opposite?

Relationship to the idea of AI coming up with black box solutions via their own method of diffuse thinking

Despite the affordances of recording, searching, tagging made by computerized note taking systems, the problem still remains what to search for or collect and how to relate the smaller parts to the whole.

customer relationship management vs. personal knowledge management (or perhaps more important knowledge relationship management, the relationship between individual facts to the overall whole) suggested by autocomplete on "knowl..."

Can zettelkasten be used for other than positivitistic methodologies?

https://www.cyberneticforests.com/ai-images

Critical Topics: AI Images is an undergraduate class delivered for Bradley University in Spring 2023. It is meant to provide an overview of the context of AI art making tools and connects media studies, new media art, and data ethics with current events and debates in AI and generative art. Students will learn to think critically about these tools by using them: understand what they are by making work that reflects the context and histories of the tools.

Sloan, Robin. “Author’s Note.” Experimental fiction. Wordcraft Writers Workshop, November 2022. https://wordcraft-writers-workshop.appspot.com/stories/robin-sloan.

brilliant!

How fitting that the amanuensis in a short story written with the help of artificial intelligence has done the opposite of what the author intended!

Wordcraft Writers Workshop by Andy Coenen - PAIR, Daphne Ippolito - Brain Research Ann Yuan - PAIR, Sehmon Burnam - Magenta

cross reference: ChatGPT

When does using an artificial intelligence-based writing tool make the writer an editor of the computer's output rather than the writer themself?

If I were going to use an AI, I'd want to plugin and give massive priority to my commonplace book and personal notes followed by the materials I've read, watched, and listened to secondarily.

Wordcraft's hallucinations can create interesting and creatively surreal suggestions.

How might one dial up or down the ability to hallucinate or create surrealism within an artificial intelligence used for thinking, writing, etc.?

Because one may need to spend an inordinate amount of time filtering through potentially bad suggestions of artificial intelligence, the time and energy spent keeping a commonplace book or zettelkasten may pay off magnificently in the long run.

Examples of artificial intelligence pushing toward pre-existing biases based on training data sets.

How to improve on this state of the art?

Eugenia Triantafyllou is talking about crutches for creativity and inspiration, but seems to miss the value of collecting interesting tidbits along the road of life that one can use later. Instead, the emphasis here becomes one of relying on an artificial intelligence doing it for you at the "hit of a button". If this is the case, then why not just let the artificial intelligence do all the work for you?

This is the area where the cultural loss of mnemonics used in orality or even the simple commonplace book will make us easier prey for (over-)reliance on technology.

Is serendipity really serendipity if it's programmed for you?

Again note the reference to magic with respect to the artificial intelligence: "the ability to conjure ideas 'out of thin air'".

Just as using a text for writing generative annotations (having a conversation with a text) is a useful exercise for writers and thinkers, creative writers can stand to have similar textual creativity prompts.

Compare Wordcraft affordances with tools like Nabokov's card index (zettelkasten) method, Twyla Tharp's boxes, MadLibs, cadavre exquis, et al.

The key is to have some sort of creativity catalyst so that one isn't working in a vacuum or facing the dreaded blank page.

The engineers behind Wordcraft refer to it "as a 'magic text editor'". This is a cop-out for many versus a more concrete description of what is actually happening under the hood of the machine.

It's also similar, thought subtly different to the idea of the "magic of note taking" by which writers are taking about ideas of emergent creativity and combinatorial creativity which occur in that space.

Is LaMDA really able to "learn higher-level concepts" or is it just a large, straight-forward information theoretic-based prediction engine?

https://pair.withgoogle.com/

People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI by doing fundamental research, building tools, creating design frameworks, and working with diverse communities.

Ippolito, Daphne, Ann Yuan, Andy Coenen, and Sehmon Burnam. “Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers.” arXiv, November 9, 2022. https://doi.org/10.48550/arXiv.2211.05030.

See also: https://wordcraft-writers-workshop.appspot.com/learn

A Google project entering the public as ChatGPT was released and becoming popular.

For additional experiences, see: https://www.robinsloan.com/newsletters/authors-note/

Author's note by Robin Sloan<br /> November 2022

PolitiFact - People are using coded language to avoid social media moderation. Is it working?<br /> by Kayla Steinberg<br /> November 4, 2021

http://www.wisdomofchopra.com/...

A random generator using Deepak Chopra tweets.

Reminiscent of https://hypothes.is/a/bzlr9l06Ee23w7voPzbY5g

A Luhmann web article from 2001-06-30!

Berzbach, Frank. “Künstliche Intelligenz aus Holz.” Online magazine. Magazin für junge Forschung, June 30, 2001. https://sciencegarden.net/kunstliche-intelligenz-aus-holz/.

Interesting to see the stark contrast in zettelkasten method here in an article about Luhmann versus the discussions within the blogosphere, social media, and other online spaces circa 2018-2022.

ᔥ[[Daniel Lüdecke]] in Arbeiten mit (elektronischen) Zettelkästen at 2013-08-30 (accessed:: 2023-02-10 06:15:58)

https://docs.google.com/document/d/1E8b-aY6R-CUMgXe0UTCsdyHWHDatBa1DaQBvdcuA_Kk/edit

AI in Education Resource Directory

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>Hypothesis</span> in Liquid Margins 38: The rise of ChatGPT and how to work with and around it : Hypothesis (<time class='dt-published'>02/09/2023 16:11:54</time>)</cite></small>

https://docs.google.com/document/d/1WpCeTyiWCPQ9MNCsFeKMDQLSTsg1oKfNIH6MzoSFXqQ/preview<br /> Policies related to ChatGPT and other AI Tools

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>Hypothesis</span> in Liquid Margins 38: The rise of ChatGPT and how to work with and around it : Hypothesis (<time class='dt-published'>02/09/2023 16:11:54</time>)</cite></small>

Foundation Models in AI

Large language models, more generally, are “foundation models”. They got the large-language name because that is where they were first applied.

Generative AI requires prompt engineering, likely a new profession

What domain experience does a prompt engineer need? How might this relate to relate to specialty in librarianship?

https://genizalab.princeton.edu/events/2022/princeton-machine-learning-and-future-philology-symposium

Was this recorded?

The Friedberg Judeo-Arabic Project contains a large corpus of Judeo-Arabic text which can be manually searched to help improve translations of texts, but it might also be profitably mined using information theoretic and corpus linguistic methods to provide larger group textual translations and suggestions at a grander scale.

Computer means can potentially be used to check or suggest potential "joins" of fragments of historical documents.

An example of some of this work can be seen in the Friedberg Genizah Project and their digital tools.

https://ojs.stanford.edu/ojs/index.php/grace/announcement/view/8

Video: https://stanford.zoom.us/rec/play/UekZ6yqC5vBZYl6OaxLLX7Vj-jTFITg0fko6ajh2Ep7z9ubA5pAA0nZ-TKsvi-Etyb9LXQxndyqv59gO.E7hQl3aJ7jmGoFFc?continueMode=true&_x_zm_rtaid=Y8gSDRJMQFigVdA9ETLRLw.1670081959153.6e53db911256d27d5172fb8866a7bc65&_x_zm_rhtaid=429

I had RSVPd to this, but the organizers totally blew it on sending out the proper zoom link.

Original event page: https://www.eventbrite.com/e/envisioning-paths-individual-collective-action-for-ethical-technology-tickets-466438639527

Description: https://events.stanford.edu/event/envisioning_paths_individual_and_collective_action_for_ethical_technology

https://meso.tzyl.nl/2022/12/05/the-history-of-zettelkasten/

If generated, it almost perfect reflects the public consensus, but does a miserable job of reflecting deeper realities.

🤔

https://meso.tzyl.nl/2022/12/04/a-two-month-experiment/

https://www.methexis.ai/join-the-collaboration

Title : Artificial Intelligence and Democratic Values: Next Steps for the United States Content : In Dartmouth University , appears AI as sciences however USA motionless a national AI policy comparing to Europe where The Council of Europe is developing the first international AI convention and earlier UE launched the European data privacy law, the General Data Privacy Regulation.

In addition, China's efforts to become “world leader in AI by 2030, as long as China is developing a digital structures matched with The one belt one road project . USA , did not contribute to UNESCO AI Recommendations however USA It works to promote democratic values and human rights and integrate them with the governance of artificial intelligence .

USA and UE are facing challenges with transatlantic data flows , with Ukrainian crises The situation became more difficult. In order to reinstate leadership in AI policy, the United States should advance the policy initiative launched last year by the Office of Science and Technology Policy (OSTP) and Strengthening efforts to support AI Bill of rights .

EXCERPT: USA believe that foster public trust and confidence in AI technologies and protect civil liberties, privacy, and American values in their application can establish responsible AI in USA. Link: https://www.cfr.org/blog/artificial-intelligence-and-democratic-values-next-steps-united-states Topic : AI and Democratic values Country : United States of America

https://namelix.com/app/

https://infiniteconversation.com/

an AI generated, never-ending discussion between Werner Herzog and Slavoj Žižek. Everything you hear is fully generated by a machine. The opinions and beliefs expressed do not represent anyone. They are the hallucinations of a slab of silicon.

https://www.robinsloan.com/notes/writing-with-the-machine/

Related work leading up to this video: https://vimeo.com/232545219

https://www.explainpaper.com/

Another in a growing line of research tools for processing and making sense of research literature including Research Rabbit, Connected Papers, Semantic Scholar, etc.

Functionality includes the ability to highlight sections of research papers with natural language processing to explain what those sections mean. There's also a "chat" that allows you to ask questions about the paper which will attempt to return reasonable answers, which is an artificial intelligence sort of means of having an artificial "conversation with the text".

cc: @dwhly @remikalir @jeremydean

https://www.supermind.design/database

https://fermat.ws/<br /> https://app.fermat.ws/

Demis Hassabis, the founder of DeepMind, classifies creativity in three ways: interpolation, extrapolation, and "true invention". He defines the first two traditionally, but gives a more vague description of the third. What exactly is "true invention"?

How can one invent without any catalyst at all? How can one invent outside of a problem's solution space? outside of the adjacent possible? Does this truly exist? Or doesn't it based on definition.

https://www.scientificamerican.com/article/information-overload-helps-fake-news-spread-and-social-media-knows-it/

Good overview article of some of the psychology research behind misinformation in social media spaces including bots, AI, and the effects of cognitive bias.

Probably worth mining the story for the journal articles and collecting/reading them.

Recall that this isn't new:

Blair, Ann M. Too Much to Know: Managing Scholarly Information before the Modern Age. Yale University Press, 2010. https://yalebooks.yale.edu/book/9780300165395/too-much-know

The new portions are the acceleration of the issue by social media and the inflammation by artificial intelligence.

https://www.re-collect.ai/

https://www.rayyan.ai/

Sparkes, M. (2021, November 19). Wikipedia tests AI for spotting contradictory claims in articles. New Scientist. https://institutions.newscientist.com/article/2298169-wikipedia-tests-ai-for-spotting-contradictory-claims-in-articles/?utm_campaign=echobox&utm_medium=social&utm_source=Twitter&utm_term=Autofeed

Oh dear god, it's worse, the writer seems to be affiliated with bundleIQ, a product that's an AI applied to the knowledge space. It's a major mistake for AI people to be playing in spaces in which they have absolutely no founding in the history of...

rose colored glasses...

comment on: https://www.youtube.com/watch?v=9OUn2-h6oVc

AI text generator, a boon for bloggers? A test report

While I wanted to investigate AI text generators further, I ended up writing a testreport.. I was quite stunned because the AI ​​text generator turns out to be able to create a fully cohesive and to-the-point article in minutes. Here is the test report.

This appears to be setting up the conditions for an artificial cognitive agent to be able to play a role (ie Artificial Intelligence)

• Optimization problem - human beings, their social system and AI - what is optimal configuration?

A promising project is Paul Bricman's Conceptarium.

Philosophical questions for AI-generated artwork

As if we needed more technology to dissolve a shared, cohesive view of reality, we need to consider how it is possible to tune the AI parameters to reflect some version of what is versus some version of how we want it to be.

Discussion on

Bellinger C, Drozdyuk A, Crowley M, Tamblyn I. Balancing Information with Observation Costs in Deep Reinforcement Learning. Proceedings of the Canadian Conference on Artificial Intelligence [Internet]. 2022 May 27; Available from: https://caiac.pubpub.org/pub/0jmy7gpd

https://twitter.com/augmented_CI

The words "beyond", "hierarchical", and "archaic" are all designed to marginalize prior thought and tools which all work, and are likely upon which this broader idea is built. This is a potentially toxic means of creating "power over" this prior art rather than a more open spirit of "power with".

Interesting sounding high level paper about the limits and constraints on general intelligence and how this might relate to the struggles AI/ML research has had historically.

Hypothesis page to discuss this high level description of DeepMind's new Gato framework.

Bret Victor shared this post to make the point that we shouldn't be worrying about sentient AI right now; that the melting ice caps are way more of a threat than AGI. He linked to this article, saying that corporations act like a non-human, intelligent entity, that has real impacts in the world today, that may be way more consequential than AI.

Ben Williamson shared this post on Twitter, saying that it's a good idea to remove the words 'artificial intelligence' and 'AI' from policy statements, etc. as a way of talking about specific details of a technology. We can see loads of examples of companies using 'AI' to obfuscate what they are really going.

AI-driven Surveillance-as-a-Service

Vumacam provides the platform, AI-driven target selection, and human review. Others subscribe to that service and add their own layers of services to customers.

While algorithmic feeds and "artificial intelligences" might control large swaths of what we see in our passive acquisition modes, we can and certainly should spend more of our time in active search modes which don't employ these tools or methods.

How might we better blend our passive and active modes of search and discovery while still having and maintaining the value of serendipity in our workflows?

Consider the loss of library stacks in our research workflows? We've lost some of the serendipity of seeing the book titles on the shelf that are adjacent to the one we're looking for. What about the books just above and below it? How do we replicate that sort of serendipity into our digital world?

How do we help prevent the shiny object syndrome? How can stay on task rather than move onto the next pretty thing or topic presented to us by an algorithmic feed so that we can accomplish the task we set out to do? Certainly bookmarking a thing or a topic for later follow up can be useful so we don't go too far afield, but what other methods might we use? How can we optimize our random walks through life and a sea of information to tie disparate parts of everything together? Do we need to only rely on doing it as a broader species? Can smaller subgroups accomplish this if carefully planned or is exploring the problem space only possible at mass scale? And even then we may be under shooting the goal by an order of magnitude (or ten)?

Research Rabbit is a search engine for academic research that was launched in August of 2021 and bills itself as "Spotify for papers." It uses artificial intelligence to recommend related papers to researchers and updates those recommendations based on the contents of one's growing corpus of interest.

Semantic Scholar is a digital tool created by the Allen Institute for Artificial Intelligence in Seattle, Washington in 2015. It's corpus is publicly available for search and is used by other tools including Connected Papers.

Is physics open or closed?

Could a play, made in a zettelkasten-like structure, be performed in a way so as to keep a consistent authorial voice?

What potential applications does the idea of opera aperta have for artificial intelligence? Can it be created in such a way as to give an artificial brain a consistent "authorial voice"?

https://elicit.org/

Frimer, J., Aujla, H., Feinberg, M., Skitka, L., Aquino, K., Eichstaedt, johannes C., & Willer, R. (2022). Incivility is Rising among American Politicians on Twitter. PsyArXiv. https://doi.org/10.31234/osf.io/2hku3

https://artsandculture.google.com/experiment/blob-opera/AAHWrq360NcGbw?cp=e30.

By changing the parameters of the AI, the output of the AI changed dramatically.

Nice that he takes a more humanistic viewpoint here rather than indicating that it will all be artificial intelligence in the future.

Apparently Persuall was embarrassed about their pro-surveillance capitalism stance and perhaps not so much for its lack of kindness and care for the basic humanity of students.

Sad that they haven't explained or apologized for their misstep.

https://web.archive.org/web/20220222022208/https://twitter.com/perusall/status/1495945680002719751

Additional context: https://twitter.com/search?q=(%40perusall)%20until%3A2022-02-23%20since%3A2022-02-21&src=typed_query

What about a standard of care for students?

Bragging about students not knowing how the surveillance technology works is unethical.<br><br>Students using accessibility software or open educational resources shouldn't be punished for accidentally avoiding surveillance. pic.twitter.com/Uv7fiAm0a3

— Ian Linkletter (@Linkletter) February 22, 2022

#annotation https://t.co/wVemEk2yao

— Remi Kalir (@remikalir) February 23, 2022

https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187

Dennis Duncan includes two indices in his book Index, A History of The, one by a professional human indexer and the second generated by artificial intelligence. He indicates that the human version is far better.

Proofreading while rewriting, structuring, or doing the thinking or creative parts of writing is a form of bikeshedding. It is easy to focus on the small and picayune fixes when writing, but this distracts from the more important parts of the work which really need one's attention to be successful.

Get your ideas down on paper and only afterwards work on proofreading at the end. Switching contexts from thinking and creativity to spelling, small bits of grammar, and typography can be taxing from the perspective of trying to multi-task.

Link: Draft #4 and using Webster's 1913 dictionary for choosing better words/verbiage as a discrete step within the rewrite.

Linked to above: Are there other dictionaries, thesauruses, books of quotations, or individual commonplace books, waste books that can serve as resources for finding better words, phrases, or phrasing when writing? Imagine searching through Thoreau's commonplace book for finding interesting turns of phrase. Naturally searching through one's own commonplace book is a great place to start, if you're saving those sorts of things, especially from fiction.

Link this to Robin Sloan's AI talk and using artificial intelligence and corpuses of literature to generate writing.

https://beta.flim.ai/

https://vimeo.com/232545219

from: Eyeo Conference 2017

• http://eyeofestival.com/2017/speaker/robin-sloan/
• https://vimeo.com/channels/eyeo2017/232545219

Description

Robin Sloan at Eyeo 2017 | Writing with the Machine | Language models built with recurrent neural networks are advancing the state of the art on what feels like a weekly basis; off-the-shelf code is capable of astonishing mimicry and composition. What happens, though, when we take those models off the command line and put them into an interactive writing environment? In this talk Robin presents demos of several tools, including one presented here for the first time. He discusses motivations and process, shares some technical tips, proposes a course for the future — and along the way, write at least one short story together with the audience: all of us, and the machine.

Notes

Robin created a corpus using If Magazine and Galaxy Magazine from the Internet Archive and used it as a writing tool. He talks about using a few other models for generating text.

Some of the idea here is reminiscent of the way John McPhee used the 1913 Webster Dictionary for finding words (or le mot juste) for his work, as tangentially suggested in Draft #4 in The New Yorker (2013-04-22)

Cross reference: https://hypothes.is/a/t2a9_pTQEeuNSDf16lq3qw and https://hypothes.is/a/vUG82pTOEeu6Z99lBsrRrg from https://jsomers.net/blog/dictionary

Croatian acapella singing: klapa https://www.youtube.com/watch?v=sciwtWcfdH4

Writing using the adjacent possible.

Corpus building as an art [~37:00]

Forgetting what one trained their model on and then seeing the unexpected come out of it. This is similar to Luhmann's use of the zettelkasten as a serendipitous writing partner.

Open questions

How might we use information theory to do this more easily?

What does a person or machine's "hand" look like in the long term with these tools?

Can we use corpus linguistics in reverse for this?

What sources would you use to train your model?

References:

• Andrej Karpathy. 2015. "The Unreasonable Effectiveness of Recurrent Neural Networks"
• Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al. "Generating sentences from a continuous space." 2015. arXiv: 1511.06349
• Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017. "A Hybrid Convolutional Variational Autoencoder for Text generation." arXiv:1702.02390
• Soroush Mehri, et al. 2017. "SampleRNN: An Unconditional End-to-End Neural Audio Generation Model." arXiv:1612.07837 applies neural networks to sound and sound production

There is an interesting difference between artificial intelligence and intelligence automation. Index cards were already doing the second by the early 1940s.

https://www.theguardian.com/commentisfree/2021/dec/06/google-silicon-valley-ai-timnit-gebru

Just because a dataset is publicly available doesn't mean that you can use it to build commercial AI software.

Why people believe Covid conspiracy theories: Could folklore hold the answer? | Coronavirus | The Guardian. (n.d.). Retrieved October 26, 2021, from https://www.theguardian.com/world/ng-interactive/2021/oct/26/why-people-believe-covid-conspiracy-theories-could-folklore-hold-the-answer

https://allevents.in/online/guest-speaker-event-how-humans-judge-machines-with-prof-cesar-hidalgo/10000171520310867

I meant to join this last week, but didn't manage. Now I'll have to watch the video after the fact:

https://teams.microsoft.com/l/meetup-join/19%3ameeting_MzVjYTc4MWItNGExNS00ZTVhLWFlYTAtMjdhOGE0OTY3MjQy%40thread.v2/0?context=%7b%22Tid%22%3a%22fbd909df-ea69-4788-a554-f24b7854ad03%22%2c%22Oid%22%3a%22a5f793d9-3a63-429f-baa0-51e6e04deb79%22%2c%22IsBroadcastMeeting%22%3atrue%7d&btype=a&role=a

A ‘Brainwashed Death Cult’: The Gamification of Conspiracy – Byline Times. (n.d.). Retrieved August 17, 2021, from https://bylinetimes.com/2021/08/10/a-brainwashed-death-cult-the-gamification-of-conspiracy/

Intestesing. Mr. Roach thinks healthcare is not doing enough to attract new types of talent (AI and emerging tech) into healthcare. We seem to be losing this talent to the technology sector.

I would agree with this point. Why work for healthcare with all of its massive demands and HIPPA and lack of people knowing what you are even building. Instead, you can go into tech, have a better quality of life, get paid so much more, and have the possibility of exiting due to a buyout from the healthcare industry.

Already I can see too many companies relying on artificial intelligence to sort and filter this material and it has the ability to cause even worse nth degree level problems.

Allowing the end user to easily control the content curation and filtering will be absolutely necessary, and even then, customer desire to do this will likely loose out to the automaticity of AI. Customer laziness will likely win the day on this, so the design around it must be robust.

Roberts, M. (n.d.). Artificial intelligence has been of little use for diagnosing covid-19. New Scientist. Retrieved 24 May 2021, from https://www.newscientist.com/article/mg25033350-100-artificial-intelligence-has-been-of-little-use-for-diagnosing-covid-19/

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>John Pavlus </span> in Melanie Mitchell Trains AI to Think With Analogies | Quanta Magazine (<time class='dt-published'>07/24/2021 17:19:52</time>)</cite></small>

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>John Pavlus </span> in Melanie Mitchell Trains AI to Think With Analogies | Quanta Magazine (<time class='dt-published'>07/24/2021 17:19:52</time>)</cite></small>

https://www.quantamagazine.org/melanie-mitchell-trains-ai-to-think-with-analogies-20210714/

Facebook AI. (2021, July 16). We’ve built and open-sourced BlenderBot 2.0, the first #chatbot that can store and access long-term memory, search the internet for timely information, and converse intelligently on nearly any topic. It’s a significant advancement in conversational AI. https://t.co/H17Dk6m1Vx https://t.co/0BC5oQMEck [Tweet]. @facebookai. https://twitter.com/facebookai/status/1416029884179271684

Johnson, Khari. ‘AI Could Soon Write Code Based on Ordinary Language’. Wired. Accessed 21 June 2021. https://www.wired.com/story/ai-write-code-ordinary-language.

Cognition and perception are closely related in humans, as the theory of embodied cognition has shown. But until the concept of embodied cognition gained traction, we had developed a pretty intellectual concept of cognition: as something located in our brains, drained of emotions, utterly rational, deterministic, logical, and so on. This is still the concept of intelligence that rules research in AI.

The truth is we do not need to have computers to excel in the things we do best, but to complement us. We shall bet on cognitive extension instead of trying to re-create human intelligence --which is a legitimate area of research, but computer scientists should leave this to cognitive science and neuroscience.

What if they're not? What if they're building an advertising machine to manipulate us into giving them all our money?

From an investor perspective, the artificial answer certainly seems sexy while using some clever legerdemain to keep the public from seeing what's really going on behind the curtain?

What if we want more serendipity? What if we don't know what we really want? Where is this in their system?

Semantic Scholar, a free, AI-powered research tool for scientific literature