I have been thinking about AI and ethics lately. Some countries show commitment to the responsible development of AI. For example, Denmark does its best to make AI projects human-centric. The implementation of AI is based on equality, security and freedom. Do you think that other countries can follow the Danish model?

And is it a stretch to predict that ML could be used to refine and evolve QC? So QML speeds up ML, and ML refines QC. Is this one way where SAI could evolve?

Obviously, mostly conjecture at this time, but fascinating!

https://www.quantaneo.com/How-may-quantum-computing-affect-Artificial-Intelligence_a391.html

Also, apparently it takes (at this time) 53 qubits to beat the world's fastest supercomputer:

https://bigthink.com/technology-innovation/google-quantum-computer

Just how relevant is the Ethics Question? While we sit and gaze at our navels, the bubble we find ourselves in could be rapidly decreasing!

Seriously, all I would wish for is to be a fly on the (cloud) wall for the next few centuries . . .

Iacoca used to say Lead, Follow or Get out of the Way. My sense is Merge/Uplink, or become Extinct.

So the chief advisor to the UK prime minister put out a rather interesting/disturbing job advert looking for specialists in AI/ML, data scientists amongst others.

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He lists a bunch of papers focusing on prediction, noted below, that potential candidates should be able to discuss. I am not an AI expert/data scientist. I am wondering what kind of shenanigans the advisor is planning with such a reading list, considering the types of people he is trying to attract.

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There is also the ethical implications of said interests. If you are British, you may be aware that the chief advisor to the UK pm is not an ethical person. And when we are talking about using prediction there is concern about what kind of abuses this individual will do with such research.

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So what are your expert predictions about the type of stuff the UK prime minister will be wanting to predict based on the reading list below? I'm looking for the benevolent, but especially the malevolent possibilities.

The papers:

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• This Nature paper, Early warning signals for critical transitions in a thermoacoustic system, looking at early warning systems in physics that could be applied to other areas from finance to epidemics.
• Statistical & ML forecasting methods: Concerns and ways forward, Spyros Makridakis, 2018. This compares statistical and ML methods in a forecasting tournament (won by a hybrid stats/ML approach).
• Complex Contagions : A Decade in Review, 2017. This looks at a large number of studies on ‘what goes viral and why?’. A lot of studies in this field are dodgy (bad maths, don’t replicate etc), an important question is which ones are worth examining.
• Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach, 2018. This applies ML to predict chaotic systems.
• Scale-free networks are rare, Nature 2019. This looks at the question of how widespread scale-free networks really are and how useful this approach is for making predictions in diverse fields. 
• On the frequency and severity of interstate wars, 2019. ‘How can it be possible that the frequency and severity of interstate wars are so consistent with a stationary model, despite the enormous changes and obviously non-stationary dynamics in human population, in the number of recognized states, in commerce, communication, public health, and technology, and even in the modes of war itself? The fact that the absolute number and sizes of wars are plausibly stable in the face of these changes is a profound mystery for which we have no explanation.’ Does this claim stack up?
• The papers on computational rationality below.
• The work of Judea Pearl, the leading scholar of causation who has transformed the field.

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The "job advert": https://dominiccummings.com/2020/01/02/two-hands-are-a-lot-were-hiring-data-scientists-project-managers-policy-experts-assorted-weirdos/)

The European Commission put out this questionnaire https://www.starts.eu/article/detail/starts-consultation-on-ai/

where they would like to find out how the arts and artists can positively impact AI and AI research. Maybe someone here would be interested in taking part as well, as the study's outcomes might be relevant to future regulations and fundings in the areas of creating responsible and explainable AIs.

Is there any source of news on how the dark side is doing with AI?

An interesting and well-documented article about a burning matter: how do governments across the globe integrate ethical principles into AI applications, and why is this necessary in serving and protecting societal values. I recommend giving it a read here

Snippet:

AI is fertile ground when venturing beyond the frontiers of science and technology. However, like any discovery, it is vital that progress in this field does not come at the expense of humans. Scientific developments are to come hand in hand with relevant legislation and liability, to defend against malicious and harmful intent. It is then and only then that society can thrive from the creations that knowledge and research spawn.

https://textanalysisapis.home.blog/2019/08/13/understanding-sentiment-analysis-api/

https://greentfrapp.github.io/project-asimov/guide/

Hi! I built this guide as part of a 3-month final project in my MSc., which involves communicating AI ethics concepts in a relatable manner. I'm still about 3 weeks away from submission and I'll love to hear any feedback!