there's no other way, understanding comes from using it, and having stuff go wrong. The scandals around algos are important in this. Scale and distribution are different beasts. Distribution does not need scale (but a network effect helps) in order to work. The need for scale in digital is an outcome of the financing structure and chosen business model, and is the power grab essentially. #openvraag hoe zet je meer focus op distributie als tegenkracht tegen de schalingshonger van actoren?

yes. never look at something 'alone'

States that, in contrast to a decade ago, now we can measure scaling, emergent capabilities, feedback loops. Interesting. - [ ] #30mins #ai-ethics werk dit uit in meer detail. Wat meet je dan, hoe kan dat er uit zien? Hoe vergelijkt dat met div beoordelingsmechanismen?

geopolitics, whether in shape of capital, tech or politics has become key, which he overlooked in 2015/8

The book did not address alignment, assumed it would sort itself out (in contrast to [[AI begincondities en evolutie 20190715140742]] how starting conditions might influence that. David recognises how algo's are also used to make diffs worse.

More detailed formulation of Gibson future is already here but distributed. Add sectors/domains. There's more here to tease out wrt my change management work. - [ ] #30mins #ai-ethics vul in met concretere voorbeelden hoe deze quote vorm krijgt

David posits questions that are all on the application side, what is the impact of using ai. There are also questions on the design side, how do we shape the tools wrt those concepts. Vgl [[AI begincondities en evolutie 20190715140742]] e.g. diff outcomes if you start from military ai params or civil aviation (much stricter), in ref to [[Novacene by James Lovelock]]

[[Toezicht houden in het AI-tijdperk by Esther van Egerschot Marco Florijn]] mbt toezicht/politieke rollen vs AI vragen. Wellicht interessant taalgebruik/framing om uit te putten?

for - quote - AI ethics - AI pets - very soon people will think that if you turn off their algorithm, you're killing their pet,

I recently came across the following, which I really like: The Artificial Intelligence Disclosure (AID) Framework.

IF you decided there were one or two situations where students were allowed to use generative AI, maybe they'd be comfortable using something like this to "admit" and disclose the use of a tool to, for instance, improve the writing of a non-native English writer?

Author moved from mitigating harm of algo systems to the moral standpoint that actively resisting, sabotaging, ending AI with attached political projects are valid reaction to harm. So he's moving from monster adaptation / cultural category adaptation to monster slaying cf [[Monstertheorie 20030725114320]]. I empathise but also wonder, bc of the mention of the political projects / structures attached, about polarisation in response to monster embracers (there are plenty) shifting the [[Overton window 20201024155353]] towards them.

Ameera Kawash (artist, researcher) def of decolonizing AI.

T. Herlau, "Moral Reinforcement Learning Using Actual Causation," 2022 2nd International Conference on Computer, Control and Robotics (ICCCR), Shanghai, China, 2022, pp. 179-185, doi: 10.1109/ICCCR54399.2022.9790262. keywords: {Digital control;Ethics;Costs;Philosophical considerations;Toy manufacturing industry;Reinforcement learning;Forestry;Causality;Reinforcement learning;Actual Causation;Ethical reinforcement learning}

• for: canonical unit, collaborative commons - missing part - open learning commons, question - process trap - natural capital

• comment

  • in this context, indyweb and Indranet are not the canonical unit, but then, it seems the model is fundamentally missing the functionality provided but the Indyweb and Indranet, which is and open learning system.
  • without such an open learning system that captures the essence of his humans learn, the activity of problem-solving cannot be properly contextualised, along with all of limitations leading to progress traps.
  • The entire approach of posing a problem, then solving it is inherently limited due to the fractal intertwingularity of reality.

• question: progress trap - natural capital

  • It is important to be aware that there is a real potential for a progress trap to emerge here, as any metric is liable to be abused

• for: AI ethics controversy - citations from Dean please!

• comment

  • Can Dean please provide the missing citations he is referring to?

• for: progress trap -AI, carbon footprint - AI, progress trap - AI - bias, progress trap - AI - situatedness

https://web.archive.org/web/20231019053547/https://www.careful.industries/a-thousand-cassandras

"Despite being written 18 months ago, it lays out many of the patterns and behaviours that have led to industry capture of "AI Safety"", co-author Rachel Coldicutt ( et Anna Williams, and Mallory Knodel for Open Society Foundations. )

For Open Society Foundations by 'careful industries' which is a research/consultancy, founded 2019, all UK based. Subscribed 2 authors on M, and blog.

A Thousand Cassandras in Zotero.

• summary
  • can we program AI to give a damn?

• for: bio-buddhism, buddhism - AI, care as the driver of intelligence, Michael Levin, Thomas Doctor, Olaf Witkowski, Elizaveta Solomonova, Bill Duane, care drive, care light cone, multiscale competency architecture of life, nonduality, no-self, self - illusion, self - constructed, self - deconstruction, Bodhisattva vow
• title: Biology, Buddhism, and AI: Care as the Driver of Intelligence
• author: Michael Levin, Thomas Doctor, Olaf Witkowski, Elizaveta Solomonova, Bill Duane, AI - ethics
• date: May 16, 2022

• source: https://www.mdpi.com/1099-4300/24/5/710/htm

• summary

  • a trans-disciplinary attempt to develop a framework to deal with a diversity of emerging non-traditional intelligence from new bio-engineered species to AI based on the Buddhist conception of care and compassion for the other.
  • very thought-provoking and some of the explanations and comparisons to evolution actually help to cast a new light on old Buddhist ideas.
  • this is a trans-disciplinary paper synthesizing Buddhist concepts with evolutionary biology

holy shit....bad!!!!!

What are all the automated decisions currently be made by AI systems globally? How to get a database/list of these?

Computational != objective! Common idea rests on lots of assumptions

It is unclear what form the "alignment property" would take, and most importantly how such a property would be evaluated especially if there's an arbitrary divide between "dangerous" and "pre-dangerous" levels of capabilities and alignment of the "dangerous" levels cannot actually be measured.

I think this is yet to be seen. Although it is true that the computer always gives the same output given the same input code, a biased network with oppressive ideologies could simply transform, instead of change, our current human judiciary enforcement of the law.

not just trained with, also trained by. is it fully transparent though? Perhaps from the trainers/tools standpoint, but users are likely to fall for the tool abstracting its origins away, ELIZA style, and project agency and thus morality on it.

Love this response

And the problem is that, even human beings are not very sensitive to how this can be done well. Because there is such diversity in human cultures, preferences, and norms, deciding whose values to prioritise is problematic.

yikes

<big>评：</big><br/><br/>「电车难题」曾引起旷日持久的讨论，而它的姊妹版「运输机难题」恐怕也一时难解。对于此类道德两难的选择困境，人们通常倾向于从自己的经验判断出发——主人公「搬动方向杆使车辆撞死一人」的行为，所受到的公众谴责要远小于主人公「站在轨道上方的天桥，为了救五人而故意把桥上的另一个人推下桥以逼停电车」的选择。那么对于「运输机难题」来说呢？还有没有比「一半机组成员跳下飞机」更优的解？<br/><br/>这样的讨论又让人联想到技术主义者在 AI 人工智能领域的意见分野：一派人认为 AI 最终的目的是取代人类，而另一派人的观点则坚信 AI 旨在增强人类（augmentation）。哪一派的话语权更大呢？答案并不重要。重要的是, be nice.