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  • AI as an Inevitable Necessity? Let’s Not Go There

    AI as an inevitable constraint? No. In conversation with Nina Benoit about liberalized markets, the failed promise of democratization, and why AI needs standards rather than special treatment – just like any other technology.

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  • A secret AI study. A biometric orb. A new internet ID.

    After researchers sparked outrage with a secret AI experiment on Reddit, the platform considers adopting Sam Altman’s World ID system via a device called the Orb. But is biometric identity the solution, or just another dubious business model?

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  • How AI Hijacks Human Connection

    AI doesn’t just train on academic or artistic content. Increasingly, it feeds on blogs, guides, and independent journalism; any content that shows human care, credibility, or craft. Summarized and displayed in search results, this content becomes invisible at the source. Welcome to a world where creators are reduced to training fodder.

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  • The Myth of AI Democratization

    Some still believe that training large language models (LLMs) on copyrighted content is a form of “democratizing knowledge.” But when you look closely at how these models actually handle the material they ingest, the picture looks a lot less heroic – and a lot more extractive.

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  • Meta’s Silent Swallowing of My Academic Legacy

    My academic legacy? A monograph, a handful of articles—and now a starring role in training Meta’s Llama 3. No royalties. No citations. Just silent swallowing by a machine. A story of vanishing recognition in the age of AI.

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  • Klarna’s AI Whiplash: From Job Cuts to Human Epiphanies

    From “AI can do all jobs” to “Humans are invaluable!”: Klarna’s AI journey is a masterclass in hype whiplash. But behind the cringe, the CEO’s rhetoric surfaces real ethical tensions. What happens when honesty about AI and jobs is no longer whispered in executive suites – but shouted?

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  • Keeping AI Weird (for Safety Reasons)

    AI makes mistakes differently from humans. And that’s a good thing. This post explores why we shouldn’t train machines to fail like humans and why weirdness might be an important safety feature of AI.

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  • Facial Recognition: Accuracy is not the Point

    Facial recognition is flawed—but should we reject it because it’s inaccurate, or because it’s immoral? This post argues why moral arguments matter more than statistics when it comes to protecting our faces, our privacy, and our civil rights.

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  • Linking Digitalization to Ethics: a Simple Outline of Some Foundations

    It shouldn’t take a scandal of the dimensions achieved by Facebook/ Cambridge Analytica to make it clear that we must not use technology blindly without asking ourselves some ethical questions, but incidents like these certainly help to raise awareness on an ever broader scale. Yet, despite an increasing amount of articles calling for integrating ethics…

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  • Why AI really needs Social Scientists

    OpenAI states that in order to assure a rigorous design and implementation of this experiment, they need social scientists from a variety of disciplines. The title immediately caught my attention given that the kind of “AI ethics” I am dealing with hinges on an interdisciplinary approach to AI. So, I sat down and spent a…

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  • Algorithmic Decision-Making and Social Division

    Reading a report on “Discrimination, Artificial Intelligence and Algorithmic Decision-Making”, I wondered to what degree algorithmic decision-making could serve to further exacerbate discrimination in already deeply divided societies. If we want AI in general and algorithmic decision-making in particular to flourish and to contribute to the common good rather than promote or exacerbate division, we…

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  • What makes AI Ethicists “the top hire companies need to succeed”?

    KPMG ranked “AI ethicist” as one of the “top 5 AI hires companies need to succeed in 2019”. That’s good news for an ‘old business ethicist’ like me. However, there is no common understanding whether we need AI ethicists in the first place, and whether creating such a profile inevitably leads to “machinewashing”. I address…

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  • The Costs of Lowering Social Standards

    In 2014 Chiquita paid their workers in Honduras private health insurance which cost them a total of 1 million USD per year. Quite a lot of money for a company close to bankruptcy. A few weeks ago they wanted to lower the level of health care services. As a result, workers went on strike for…

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  • Ethics in the Tech Industry: What makes it so Distinctive?

    Kate O’Neill is a global thought leader, author, keynote speaker, strategic advisor, and “tech humanist”. We talked about connecting the dots between AI ethics, privacy, climate change, CSR, ESG, contact tracing, carbon offsetting and much more, including quite some laughter.

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  • Business is there to Make Life Better. But How?

    As part of his series “Interviews with global leaders in the field of Artificial Intelligence” I spoke with Johan Steyn about AI ethics, privacy, contact tracing, buiness ethics, CSR, etc. – live from my kitchen table.

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  • Ethical Debates sparked by COVID: Thoughts at the UNESCO Forum

    UNESCO Forum invited me as a speaker to share my thoughts on the Covid-19 crisis. The pandemic has sparked fundamental ethical debates. Think of the terrifying reports from hospitals in Italy in Spring 2020. Intensive care units were overrun with patients. There were not enough ventilators. And suddenly we asked ourselves: What is the value…

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  • On Teaching Artificial Intelligence & Ethics

    The Montreal AI Ethics Institute interviewed me, along with my ForHumanity colleagues Merve Hickok and Ryan Carrier, about our thoughts on teaching AI and ethics. I recommend keeping AI ethics as applied as possible and inspiring people to think about what that means for their own work experience.

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  • There is no Responsible Tech without Accountability

    There is a divide between those working on Responsible Tech inside companies and those criticizing from the outside. We need to bridge the two worlds, which requires more open-mindedness and the willingness to overcome potential prejudices. The back and forth between ‘ethics washing’ and ‘ethics bashing’ is taking up too much space.

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  • AI and Sustainability: a Solution or Part of the Problem?

    Environmental sustainability is one of the most promising domains to deploy ‘AI for Good’. The environment is an excellent use case for collecting and analyzing data that help us to better understand and address key environmental challenges. In contrast to the use of AI in ‘human settings’, you typically don’t run into problems of privacy…

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