Noteworthy Information
Amsterdam and Helsinki launch algorithm registries to bring transparency to public deployment of AI

European governments never fail to surprise the world with their innovative minds. Such registries can empower citizens and give them a way to evaluate, examine, or question governments’ applications of AI.

Amazon: How Bezos built his data machine

People love convenience and Amazon has prospered by obsessing about how to anticipate our wants before we’re even aware of them. Here is a very detailed news column on how and why Amazon collects data about you.

A Robot Wrote This Article. Are You Scared Yet, Human?

This week the Guardian published an essay written by GPT-3, OpenAI's language generator, calling it "a cutting edge language model that uses machine learning to produce human like text. It takes in a prompt, and attempts to complete it." For this esssay, the essay was fed the prompt, "I am not a human. I am Artificial Intelligence. Many people think I am a threat to humanity. Stephen Hawking has warned that AI could 'spell the end of the human race.' I am here to convince you not to worry. Artificial Intelligence will not destroy humans. Believe me." Here's what the AI wrote.

Climate Change, Personal Data & AI

Practical use of personal data and AI to save the planet. Using AI algorithm to turn personal photos of forest and nature into a blend of fire and ash to help us visualize the issues of climate change.

Don’t ask if artificial intelligence is good or fair, ask how it shifts power

It is not uncommon now for AI experts to ask whether an AI is ‘fair’ and ‘for good’. But ‘fair’ and ‘good’ are infinitely spacious words that any AI system can be squeezed into. The question to pose is a deeper one: how is AI shifting power?

Cyberbullying Detection with Fairness Constraints

Cyberbullying is a widespread adverse phenomenon among online social interactions in today's digital society. While numerous computational studies focus on enhancing the cyberbullying detection performance of machine learning algorithms, proposed models tend to carry and reinforce unintended social biases. In this study, we try to answer the research question of "Can we mitigate the unintended bias of cyberbullying detection models by guiding the model training with fairness constraints?".

Shaping the Terrain of AI Competition

How should democracies effectively compete against authoritarian regimes in the AI space? This report offers a “terrain strategy” for the United States to leverage the malleability of artificial intelligence to offset authoritarians' structural advantages in engineering and deploying AI.

AI Needs Your Data—and You Should Get Paid for It

A new approach to training artificial intelligence algorithms involves paying people to submit medical data, and storing it in a blockchain-protected system.

Beyond a Human Rights-based approach to AI Governance

This paper discusses the establishment of a governance framework to secure the development and deployment of “good AI”, and describes the quest for a morally objective compass to steer it.

AI Fairness

Ruoss et al. published the first method to train AI systems with mathematically provable certificates of individual fairness. Full source code is available on Github.

Europe is fighting tech battle with one hand tied behind its back

New proposals around data and artificial intelligence will be subject to restrictions that rivals in China and the United States do not face.

The new IKEA Data Promise (Video: 10:37)

Companies discover data ethics as part of their corporate communications: IKEA promises to embed data ethics into all their processes.

Preprint: Alternative personal data governance models

The not-so-secret ingredient that underlies all successful Artificial Intelligence / Machine Learning (AI/ML) methods is training data. There would be no facial recognition, no targeted advertisements and no self-driving cars if it was not for large enough data sets with which those algorithms have been trained to perform their tasks. Given how central these data sets are, important ethics questions arise: How is data collection performed? And how do we govern its' use? This chapter – part of a forthcoming book – looks at why new data governance strategies are needed; investigates the relation of different data governance models to historic consent approaches; and compares different implementations of personal data exchange models.

How Big Tech Manipulates Academia to Avoid Regulation

A Silicon Valley lobby enrolled elite academia to avoid legal restrictions on artificial intelligence.

A free online introduction to artificial intelligence for non-experts

The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.

Challenging algorithmic profiling: The limits of data protection and anti-discrimination in responding to emergent discrimination

Interesting article using intersectional analysis do define and recommend mitigations to emergent discrimination in algorithmic systems.

Emotion-detecting tech ’must be restricted by law’

A US-based AI institute says that the science behind the technology rests on “shaky foundations”.

Recommendations on the Ethical Use of Artificial Intelligence by the Department of Defense

The United States Department of Defense (DoD) enduring challenge is to retain a technological and military advantage while upholding and promoting democratic values, working with our allies, and contributing to a stable, peaceful international community. DoD’s development and use of artificial intelligence (AI) reflects this challenge.
The Defense Innovation Board (DIB) recommends five AI ethics principles for adoption by DoD, which in shorthand are: responsible, equitable, traceable, reliable, and governable. These principles and a set of recommended actions in support of them are described in this document.

The (not so) Global Forum on AI for Humanity

Earlier this week, I traveled to Paris to attend the Global Forum on Artificial Intelligence for Humanity (GFIAH). The by-invitation event featured one day of workshops addressing issues such as AI and culture, followed by a two days of panels on developing trustworthy AI, data governance, the future of work, delegating decisions to machines, bias and AI, and future challenges. The event was a part of the French government's effort to take the lead on developing a new AI regulatory framework that it describes as a 'third way', distinct from the approach to AI in China and the United States.

How AI and Data Could Personalize Higher Education

Artificial intelligence is rapidly transforming and improving the ways that industries like healthcare, banking, energy, and retail operate. However, there is one industry in particular that offers incredible potential for the application of AI technologies: education. The opportunities — and challenges — that the introduction of artificial intelligence could bring to higher education are significant.

EU guidelines on ethics in artificial intelligence: Context and implementation (PDF)

You may have seen the EU Guidelines on Ethics in AI. As I believe we are entering in a 'regulating AI debate', it's worth sharing it here.

The Algorithmic Colonization of Africa

Startups are importing and imposing AI systems founded on individualistic and capitalist drives. “Mining” people for data is reminiscent of the colonizer attitude that declares humans as raw material.

AI Needs Your Data—and You Should Get Paid for It

A new approach to training artificial intelligence algorithms involves paying people to submit medical data, and storing it in a blockchain-protected system.


Questions Asked
How do you train a personal AI?

If a benefit of PersonalAI is privacy, where do you get the training data from? @Iain and @Oguzhan Gencoglu joined the discussion and many interesting points were raised as well as current solutions referenced.

Explainable AI related projects?

Just talked to the key persons from Fujitsu's team today. They are involved with implementing Explainable AI. Wondering if there are any MyData experts doing Explainable AI related projects?

Make AI optional?

My one major requirement for ethical AI: all services that utilize/incorporate AI modeling of me must allow me to optionally disable AI. I.e. opt out of the AI modeling of me. @Oguzhan Gencoglu mentioned however that this might not be possible.

Comment on the human rights impacts of algorithmic systems

The Steering Committee on Media and Information Society (CDMSI) invites comments from the public on one draft text that was prepared by one of its sub-ordinate bodies and is meant to be adopted by the Committee of Ministers in early 2020. The draft recommendation of the Committee of Ministers to member states on the human rights impacts of algorithmic systems was prepared by the Committee of Experts on Human Rights Dimensions of Automated Data Processing and Different Forms of Artificial Intelligence (MSI-AUT). The experts will meet again in September to review all comments received and to finalise the draft ahead of its review by the CDMSI in December. Comments should be provided through email.

Test-driving a couple of ideas

What’s your first reaction to the twin claims that super-human, bias-free AI (let alone AGI) is not a) morally optimal nor b) possible? (The two claims are separate but linked. The issue at hand is whether we should try to get rid of bias and hence: a) is it morally imperative to get rid of bias and b) is it even possible to get rid of it.)


eszköz
Alt.ai

Personal Artificial Intelligence

Machine Intelligence Research Institute

Foundational mathematical research to ensure smarter-than-human artificial intelligence has a positive impact.

OpenMined

OpenMined is an open-source community whose goal is to make the world more privacy-preserving by lowering the barrier-to-entry to private AI technologies.

Saidot

World's first AI transparency platform: Start making your AI trusted today.

Silo.ai

Build a world with safe human-centric AI that frees the human mind from manual labour and empowers human creativity.