Digital Ethics

For decades, the conventional wisdom about Silicon Valley was that it leaned progressive. And by many measures (like donations by Big Tech employees to political candidates), the industry has been…

AI is only as good as the algorithm that operates it, the data that trains it and the law that underpins it. If these are ineffective, as with robo-debt, then calamity can ensue.

Product First is a failure. Sustainable value comes from the pursuit of strong Customer and Employee First cultures.

TikTok accounts are posting artificial intelligence-generated clips of murder victims — mostly children — describing their own ghastly demise.

Artists are worried that their work is being fed into AI systems and are taking legal action.

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Excited that our #FAccT paper on Regulating ChatGPT has now been officially published in the proceedings – open access for all! In the main paper, we analyze…

Contractors in Kenya say they were traumatized by effort to screen out descriptions of violence and sexual abuse during run-up to OpenAI’s hit chatbot.

On July 21, 2023, in a photo op featuring only men in suits, President Biden announced that seven companies (Amazon, Anthropic, Google…

Opinion: Worldcoin is no radical new financial system, and certainly not one aimed at equality or fairness.

"Legal uncertainty" over models means many devs can't establish "appropriate rights."

With drought spreading around the globe, battles over water are erupting between AI companies seeking more computing power and communities where their facilities are located.

People are turning to chatbot impersonations of lost loved ones to help them grieve. Will AI help us live after we’re dead?

Because of a bad facial recognition match and other hidden technology, Randal Reid spent nearly a week in jail, falsely accused of stealing purses in a state he said he had never even visited.

This startup wants to help millions of people whose languages are marginalized online gain better access to AI tools

Academia.edu is a platform for academics to share research papers.

The work of building public knowledge bases of AI failures can’t happen without rigorous and practical taxonomies. Check out this new report on AI harms…

With politicians struggling to curb AI harms, it’s boom time for tech lawyers.

It was only a matter of time before the Federal Trade Commission (FTC) initiated a law enforcement investigation focusing on artificial intelligence (AI).

The US already has a road map for the deployment of AI systems. Biden's promised executive order just needs to put these guidelines into practice.

With drought spreading around the globe, battles over water are erupting between AI companies seeking more computing power and communities where their facilities are located.

Companies that use AI know that they need to worry about ethics, but when they start, they tend to follow the same broken three-step process: They identify ethics with “fairness,” they focus on bias, and they look to use technical tools and stakeholder outreach to mitigate their risks. Unfortunately, this sets them up for failure. When it comes to AI, focusing on fairness and bias ignores a huge swath of ethical risks; many of these ethical problems defy technical solutions. Instead of trying to reinvent the wheel, companies should look to the medical profession, and adopt internal review boards (IRBs). IRBs, which are composed of diverse team of experts, are well suited to complex ethical questions. When given jurisdiction and power, and brought in early, they’re a powerful tool that can help companies think through hard ethical problems — saving money and brand reputation in the process.

“GPT-4, being trained off of our own textual communication, shows the same — or maybe even more exaggerated — racial and sex biases as humans" in health care.

The technology giant will stop offering automated tools that predict a person’s gender, age and emotional state and will restrict the use of its facial recognition tool.

Amid a growing call for governments to rein in the use of the technology, Microsoft became the first tech giant to join the chorus.

Dr. Alex Hanna from the Distributed AI Research (DAIR) Institute explains some of the causes of gender and racial bias in AI and discusses using a community- and value-based approach for AI development to improve equity outcomes.

The application of face recognition technology in the criminal justice system threatens to perpetuate racial inequality.