Apple has hired former Google AI scientist Samy Bengio, who resigned from the Big G following the controversial firing of ethics researcher Timnit Gebru.

Bengio will lead a new AI research unit and report to fellow ex-Googler John Giannandrea, Reuters reports .

In his role at Google, Bengio oversaw hundreds of workers and was a strong supporter of Gebru and Margaret Mitchell, who co-led the ethical AI teams before their terminations.

Gebru was fired in December after a fallout with management over a research paper she co-authored on the risks of large-scale language models, which are used in many Google products. Mitchell was sacked in February for using automated scripts to find messages showing mistreatment of Gebru.

Their sudden departures sent shockwaves across the AI community and sparked an internal backlash about ethics and diversity.

Bengio was among their most prominent defenders at Google. In a Facebook post published in the wake of Gebru’s firing, he said he was “stunned by what just happened.”

His own responsibilities were cut in the aftermath, when Google reorganized its responsible AI unit and appointed Marian Croak to lead it.

Bengio resigned from Google in March after around 14 years at the company. While he didn’t mention the firings in his farewell letter to staff, sources told Reuters that they influenced his decision to quit.

The distinguished computer scientist, who helped build Google Brain, will now join another tech giant that’s investing heavily in machine learning.

Apple acquired more AI companies than anyone else between 2016 and 2020, according to a recent study by GlobalData. The market research firm said many of the deals were focused on improving Siri.

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Encouraging women in tech is essential to protect society against AI bias

Encouraging women in AI has never been more urgent. A study by the World Economic Forum noted a gender disparity of 78 percent male versus 22 percent female in AI and data science. This disparity isn’t just a challenge within the workforce. It reflects a highly nuanced issue that goes beyond any single workplace and if not addressed will have highly negative implications for society.

We have seen a lot of work to encourage girls and women to become interested in STEMand address gaps in digital skills at an earlier age than in the past. Yet now, there appears to be less effort to support women as they transition from higher education into a sustainable career in tech. This is a challenge for the industry. But the real problem is that as AI becomes ubiquitous in daily life, without a technology workforce that accurately reflects the structure of society, AI-based decisions are constrained by the limited societal and cultural biases of their designers. The impact of such homogeneity in AI decisions and bias has already been seen in examples such as the automation of credit card and mortgage applications, to resume screening and other areas.

The industry challenge is not due to a lack of skills. Research from the Turing Institute suggests women are trailing behind men with industry-relevant skills such as computer science, data preparation and exploration, general-purpose computing, databases, big data, machine learning, statistics, and mathematics. Yet much of this is not due to formal skills, but rather confidence by women in stating these abilities during recruitment and in the workplace. In the tech world where technical skills are needed, soft skills are sometimes dismissed but in order to move forward, there needs to be a greater focus on leadership and mentorship to build confidence and encourage a more diverse workforce. We say that stereotypes must be combatted from a young age yet a gap remains. For example, within the tech sector, women generally have higher levels of formal education than their male counterparts yet academic citations are fewer suggesting there is a lack of confidence in sharing academic knowledge. The Turing Institute finds that only 20 percent of UK data and AI researchers on Google Scholar are women. Of the 45 researchers with more than 10,000 citations, only five were women.

When I say that women need to have mentors and role models, I write from firsthand experience. It was only after winning a mathematics modeling competition in university that I considered a related career. This inspired me to write a blog on machine learning algorithms . The easy-to-understand method employed helped the blog garner over 5 million views, and eventually led to a career in programming. When I became a programmer and found myself working as the only woman in a room of men typically 10-15 years older, I struggled to relate and realized the need for a community of like-minded people.

In April 2020 I started to manage operations for MindSpore, an AI framework developed by Huawei, just as it became open source. MindSpore is Huawei’s alternative AI framework to Google’s TensorFlow and Facebook’s PyTorch with comparable capabilities but 20 percetn fewer lines of code. Launched in September 2019, it is endorsed by major universities including Peking University, University of Edinburgh, and Imperial College. Today, MindSpore boasts over 1.3 million downloads and an interactive community indicated by over 19,000 issues, over 52,000 pull requests, and over 16,000 stars (the equivalent of a ‘like’ among developers).

In 2021, open-source component downloads grew 73 percent YOY. With the rapid growth in the global adoption of open source technology, diversity in open source communities is also increasing . The MindSpore Women in Tech Community emphasizes seminar-like gatherings which provide women a safe space to discuss the challenges they face in the workplace. Mentoring is important. For example, in 2020, when the community was just in its infancy, a student at one of our events explained she was getting good grades but was worried about a career in programming. She sought advice from more senior programmers and tech leaders. By the time she graduated she had no need to worry and was able to choose from one of several offers. Not only did she feel more confident but was able to give back to the community by sharing her experience with new students, those who were now in the position she had been the previous year. It is experiences like this that will keep women in tech. When they stay, tech also benefits.

But encouraging women isn’t simply about creating diversity within the industry to enable greater gender balance. The benefits stretch beyond the sector and into the societal benefits. With the digitalization of many traditional sectors, the pervasive nature of AI demands that it not only provides efficiency but is also inclusive. It is only by broadening the pool of talent that we can avoid data-led decisions skewed by bias . Establishing communities that actively foster participation and diverse voices is an important step.

Bias in AI starts with the initial formulation of problems. The questions are naturally constrained by the experiences of the designers and programmers. This in turn impacts the quality of the data and the way it is handled. So what will be the societal impact if there is not greater diversity?

User experience (UX) for women will be not be as intuitive if it is there is not greater input at the design stage.

Economic discrimination whether assigning women’s resumes to lower paid jobs and access to financial resources will have a long-term impact.

Societal resources will be distributed unfairly whether affecting education, healthcare, or even safety.

Women will lose decision-making capabilities for fundamental day-to-day as decisions.

So in conclusion, now that our lives are digitally-driven, we must ensure that women can enjoy the benefit of technology for generations to come rather than be negatively impacted.

This article was originally published by Xiaoman Hu on TechTalks , a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. You can read the original article here .

Scientists created a biological quantum circuit in grisly experiment with tardigrades

An international team of researchers are claiming to have performed the first ever experiment successfully ‘quantum entangling’ a multi-celled organism.

The team, whose research was recently published in a pre-print paper , says it’s managed to place a tardigrade – a tiny critter affectionately known as a “water bear” – in a state of quantum entanglement between a pair of superconducting qubits.

In other words: the researchers managed to put a tardigrade in a state where it was directly connected to the qubits in such a way that anything that happens to the water bear or the qubits would simultaneously affect all three.

This is a fundamental property of quantum computing. But this kind of quantum function usually only occurs with particle-sized objects. Researchers have put single-celled organisms in a state of quantum entanglement before, but this would mark the first time scientists have done so with a complex biological organism.

Eureka?

There is, however, some debate as to the significance of the team’s efforts. Per the researchers’ paper:

There’s a lot to unpack there, but first and foremost: other physicists are being critical of this work early due to what appears to be a loose definition of “entanglement.”

As spotted by Live Science’s Brandon Specktor , the buzz on social media appears to be entirely skeptical:

But, as Specktor also points out, this is all likely to get sorted in peer-review. For now, let’s talk about the experiment itself.

The nightmare before Christmas

Tardigrades are among the most resilient creatures we know of. They can enter a state of suspended animation where they have no observable biological functions in order to survive in extremely hostile environments.

It’s for this reason the scientists chose to attempt integrating them with quantum bits in a circuit. The idea’s pretty basic. You freeze the tardigrades to the point that they’re next to absolute zero, and then you can put them in a state of entanglement just like any other super-cold particle.

However, because the tardigrades are living beings, the story’s a bit more visceral than your standard “we entangled several photons” variety of experiment.

According to team’s paper, these particular tardigrades were “collected in February 2018 from a roof gutter in Niva, Denmark.”

So, to sum up, a group of humans in white coats kidnapped a bunch of cute little water bears, who were already living in a literal gutter, and then exposed them to the coldest temperatures a tardigrade’s ever experienced before forcing them into a three-way entanglement with superconducting qubits.

The team was able to revive one of the tardigrades that were successfully involved in what they’re calling entanglement. But, as for the others, the researchers wrote “we wish to point out that it is very important for the revival of the animal to change the external temperature and pressure gently.”

Rest in power little science bears, we’ll never forget you.

Further reading: Physicists might have created quantum entanglement in bacteria