#AIBias

The tech bias: why Silicon Valley needs social theory

Photo by Ramin Talaie/Corbis/Getty Image

In the summer of 2017, a now infamous memo came to light. Written by James Damore, then an engineer at Google, it claimed that the under-representation of women in tech was partly caused by inherent biological differences between men and women.

That Google memo is an extreme example of an imbalance in how different ways of knowing are valued.

Silicon Valley tech companies draw on innovative technical theory but have yet to really incorporate advances in social theory.

Social theorists in fields such as sociology, geography, and science and technology studies have shown how race, gender and class biases inform technical design.

So there’s irony in the fact that employees hold sexist and racist attitudes, yet ‘we are supposed to believe that these same employees are developing “neutral” or “objective” decision-making tools’, as the communications scholar Safiya Umoja Noble at the University of Southern California argues in her book Algorithms of Oppression (2018).

If tech companies are serious about building a better society, and aren’t just paying lip service to justice for their own gain, they must attend more closely to social theory.

If social insights were easy, and if practice followed readily from understanding, then racism, poverty and other debilitating systems of power and inequality would be a thing of the past.

New insights about society are as challenging to produce as the most rarified scientific theorems – and addressing pressing contemporary problems requires as many kinds of knowers and ways of knowing as possible.

Source: aeon



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Put Humans at the Center of AI

As the director of Stanford’s AI Lab and now as a chief scientist of Google Cloud, Fei-Fei Li is helping to spur the AI revolution. But it’s a revolution that needs to include more people. She spoke with MIT Technology Review senior editor Will Knight about why everyone benefits if we emphasize the human side of the technology.

Why did you join Google?

Researching cutting-edge AI is very satisfying and rewarding, but we’re seeing this great awakening, a great moment in history. For me it’s very important to think about AI’s impact in the world, and one of the most important missions is to democratize this technology. The cloud is this gigantic computing vehicle that delivers computing services to every single industry.

What have you learned so far?

We need to be much more human-centered.

If you look at where we are in AI, I would say it’s the great triumph of pattern recognition. It is very task-focused, it lacks contextual awareness, and it lacks the kind of flexible learning that humans have.

We also want to make technology that makes humans’ lives better, our world safer, our lives more productive and better. All this requires a layer of human-level communication and collaboration.

When you are making a technology this pervasive and this important for humanity, you want it to carry the values of the entire humanity, and serve the needs of the entire humanity.

If the developers of this technology do not represent all walks of life, it is very likely that this will be a biased technology. I say this as a technologist, a researcher, and a mother. And we need to be speaking about this clearly and loudly.

Source: MIT Technology Review



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DeepMind Ethics and Society hallmark of a change in attitude

The unit, called DeepMind Ethics and Society, is not the AI Ethics Board that DeepMind was promised when it agreed to be acquired by Google in 2014. That board, which was convened by January 2016, was supposed to oversee all of the company’s AI research, but nothing has been heard of it in the three-and-a-half years since the acquisition. It remains a mystery who is on it, what they discuss, or even whether it has officially met.

DeepMind Ethics and Society is also not the same as DeepMind Health’s Independent Review Panel, a third body set up by the company to provide ethical oversight – in this case, of its specific operations in healthcare.

Nor is the new research unit the Partnership on Artificial Intelligence to Benefit People and Society, an external group founded in part by DeepMind and chaired by the company’s co-founder Mustafa Suleyman. That partnership, which was also co-founded by Facebook, Amazon, IBM and Microsoft, exists to “conduct research, recommend best practices, and publish research under an open licence in areas such as ethics, fairness and inclusivity”.

Nonetheless, its creation is the hallmark of a change in attitude from DeepMind over the past year, which has seen the company reassess its previously closed and secretive outlook. It is still battling a wave of bad publicity started when it partnered with the Royal Free in secret, bringing the app Streams to active use in the London hospital without being open to the public about what data was being shared and how.

The research unit also reflects an urgency on the part of many AI practitioners to get ahead of growing concerns on the part of the public about how the new technology will shape the world around us.

Source: The Guardian



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Why we launched DeepMind Ethics & Society

We believe AI can be of extraordinary benefit to the world, but only if held to the highest ethical standards.

Technology is not value neutral, and technologists must take responsibility for the ethical and social impact of their work.

As history attests, technological innovation in itself is no guarantee of broader social progress. The development of AI creates important and complex questions. Its impact on society—and on all our lives—is not something that should be left to chance. Beneficial outcomes and protections against harms must be actively fought for and built-in from the beginning. But in a field as complex as AI, this is easier said than done.

As scientists developing AI technologies, we have a responsibility to conduct and support open research and investigation into the wider implications of our work. At DeepMind, we start from the premise that all AI applications should remain under meaningful human control, and be used for socially beneficial purposes. 

So today we’re launching a new research unit, DeepMind Ethics & Society, to complement our work in AI science and application. This new unit will help us explore and understand the real-world impacts of AI. It has a dual aim: to help technologists put ethics into practice, and to help society anticipate and direct the impact of AI so that it works for the benefit of all. 

If AI technologies are to serve society, they must be shaped by society’s priorities and concerns.

Source: DeepMind


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Intelligent Machines Forget Killer Robots—Bias Is the Real AI Danger

John Giannandrea – GETTY

John Giannandrea, who leads AI at Google, is worried about intelligent systems learning human prejudices.

… concerned about the danger that may be lurking inside the machine-learning algorithms used to make millions of decisions every minute.

The real safety question, if you want to call it that, is that if we give these systems biased data, they will be biased

The problem of bias in machine learning is likely to become more significant as the technology spreads to critical areas like medicine and law, and as more people without a deep technical understanding are tasked with deploying it. Some experts warn that algorithmic bias is already pervasive in many industries, and that almost no one is making an effort to identify or correct it.

Karrie Karahalios, a professor of computer science at the University of Illinois, presented research highlighting how tricky it can be to spot bias in even the most commonplace algorithms. Karahalios showed that users don’t generally understand how Facebook filters the posts shown in their news feed. While this might seem innocuous, it is a neat illustration of how difficult it is to interrogate an algorithm.

Facebook’s news feed algorithm can certainly shape the public perception of social interactions and even major news events. Other algorithms may already be subtly distorting the kinds of medical care a person receives, or how they get treated in the criminal justice system.

This is surely a lot more important than killer robots, at least for now.

Source: MIT Technology Review



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