How to Survive as an AI Ethicist

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It has never been more important for companies to ensure that their AI systems work safely, especially when there are new laws to hold them accountable. lag.

As a result, those working in this field suffer as a resultPiece. Organizations place enormous pressure on individuals to fix large, systemic problems without proper support, while they frequently face gay criticism. harshly online.

The issue also feels very personal — AI systems often reflect and exacerbate the worst aspects of our society, such as racism and sexism. The technologies at issue range from facial recognition systems that classify Blacks as gorillas to deepfake software used to create pornographic videos of women who disagree. Dealing with these issues can be especially taxing for women, people of color, and other marginalized groups, who tend to focus on AI ethical jobs.

I spoke to a range of ethics-AI practitioners about the challenges they face in their work, and one thing is clear: burnout is real and it harms the entire field. Read my story here.

Two of the people I spoke to in the story were pioneers of applied AI ethics: Margaret Mitchell and Rumman Chowdhury, now at Hugging Face and Twitter. Here are their top tips for surviving in the industry.

1. Be your own advocate. Despite the growing mainstream awareness of the risks posed by AI, ethologists still find themselves struggling to be recognized by their peers. Historically, the culture of machine learning has not been great at acknowledging human needs. “No matter how confident or loud everyone in the meeting is [who are] say or say the opposite of what you’re doing—it doesn’t mean they’re right,” says Mitchell. “You have to be prepared to be an advocate for your own work.”

2. Slow and steady wins the race. inside story, Chowdhury says it’s exhausting to follow every debate on social media about the possible harmful side effects of new AI technologies. Her advice: It’s okay not to get into every argument. “I’ve been in here long enough to see the same narrative cycle over and over again,” says Chowdhury. “You’re better off focusing on your work and finding something solid even if you’re missing two or three cycles of hype.”

3. Don’t be a martyr. (It’s not worth it.) AI ethicists have a lot in common with activists: their work is driven by passion, idealism, and a desire to make the world a better place. But there’s nothing noble about taking a job in a company that runs counter to your own values. “No matter how popular the company is, it’s not worth being in a work situation where you don’t feel like the entire company, or at least a significant part of your company, is trying to,” says Chowdhury. try to do this with you. “Your job is not to get paid to point out problems. Your job is to help them make their product better. And if you don’t believe in the product, don’t work there.”

Deeper learning

Machine learning can dramatically speed up the search for new metals

Machine learning could help scientists develop new metals with useful properties, such as resistance to extreme temperatures and rust resistance, according to new research. This could be useful in many areas — metals that perform well at lower temperatures could improve spacecraft, for example, while corrosion-resistant metals could be used for boats and submarines. .

Why is this important: The discovery could help pave the way for more use of machine learning in materials science, a field that still relies heavily on laboratory testing. In addition, the technique can be adapted for exploration in other fields, such as chemistry and physics. Read more from Tammy Xu here.

Learn more deeply

The development of AI

On Thursday, November 3, MIT Technology Review senior editor on AI, William Heaven, will ask AI celebrities like Yann LeCun, chief AI scientist at Meta; Raia Hadsell, senior director of robotics research and development at DeepMind; and Ashley Llorens, hip-hop artist and distinguished scientist at Microsoft Research, on stage at our flagship event, EmTech.

Agenda:They will discuss the way forward for AI research, the ethics of responsible AI development and use, the impact of open collaboration, and the most realistic end goal for artificial intelligence in general. . Registerhere.

LeCun is often referred to as one of the “gods of deep learning”. Will and I said with LeCun earlier this year when he announced his bold proposal for how AI could achieve human-level intelligence. LeCun’s vision includes bringing together old ideas, such as brain-inspired cognitive architecture, and combining them with deep learning technology.

Bits and bytes

Shutterstock will start selling AI-generated images
The stock image company is partnering with OpenAI, the company that created DALL-E. Shutterstock is also launching a fund to reimburse artists whose work is used to train AI models. (The Verge)

UK Information Commissioner says emotional recognition is BS
In the first from a regulator, the UK’s information commissioner said companies should avoid “pseudo-scientific” AI technology, which is claimed to be able to detect human emotions or has risk of fines. (Guardians)

Alex Hanna leaves Google to try to save the future of AI
MIT Technology Review profiled Alex Hanna, who left Google’s ethical AI team earlier this year to join the Distributed AI Research Institute (DAIR), which aims to challenge the existing understanding of AI. through a community-focused, bottom-up approach to research. The Institute is the brainchild of Hanna’s former boss, Timnit Gebru, who was fired by Google at the end of 2020. (MIT Technology Review)

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