What women think about AI

Early this month, the Pew Research Centre published the findings of a survey revealing a significant fact that most of us would have had a gut feeling about -- that women think differently about technologies like artificial intelligence (AI) compared to men. The centre surveyed 10,260 US adults from 1-7 November for this analysis. Here are a few conclusions from the report.

     

1. More concern over AI: Women in the U.S. are less likely than men to say that technology has had a mostly positive effect on society (42% vs 54%). Further, women are less likely than men to say they feel more excited than concerned about the increased use of AI computer programs in daily life (13% vs 22%).

2. Not exactly happy with driverless cars: Roughly four-in-ten men (37%) say driverless cars are a good idea for society, while 17% of women say the same. Women are also not convinced that driverless cars are safe. When asked about the widespread use of these cars would have on the number of people killed or injured in traffic accidents, about half of men (49%) said it would decrease the number of people killed or injured, compared with three-in-ten women who felt the same.

3. Indecision: Facial recognition is another area where there’s a marked difference in thinking. Women, for instance, are more likely than men to say they are not sure whether particular AI applications are a good or bad idea for society. Some 34% of women are unsure whether social media algorithms to find false information are a good or bad idea, compared with 26% of men. Likewise, when it comes to using face recognition by police, 31% of women are unsure whether it is a good or bad idea, compared with 22% of men.

4. Wanting more inclusion: Women are also more likely to support the inclusion of a wider variety of groups in AI design. For example, two-thirds of women (67%) say it’s extremely or very important for social media companies to include people of different genders when designing social media algorithms to find false information, compared with 58% of men. Women are also more likely to say it is important that different racial and ethnic groups are included in the same AI design process (71% vs 63%).

Of course, the 3 August note was US-centric but would the conclusion be radically different if the survey was conducted in some other country? I’m no expert in this field, but given that AI is a male-dominated field and that most AI research and development is predominantly in the hands of men, it’s safe to conclude that this is one of the reasons why women view AI with suspicion.

Few reasons for this Thinking Divide

A 2019 UNESCO report, for instance, pointed out that women represented only 29% of science R&D positions globally and were already 25% less likely than men to know how to leverage digital technology for basic uses. A year later, a World Economic Forum (WEF) report revealed that women make up only 26% of data and AI positions in the workforce. The Stanford Institute for Human-Centered AI’s 2021 AI Index Report found that women make up just 16% of tenure-track faculty focused on AI globally.

India is no different. According to a 2020 United Nations report, nearly 40% of STEM graduates from India are women, which is among the highest in the world. However, only 14% of the country’s 280,000 scientists, engineers and technologists are female, exposing the yawning gap in the female talent we see in the workforce.

Researchers have repeatedly pointed out that AI and machine learning models would always produce biased results as long as AI continues to be a male-dominated field. Most women, according to a 2021 Deloitte survey, feel they are not treated equally as men in AI, which prompts them to leave the field. This year a UNESCO report has made six suggestions to improve the percentage of women working in AI -- reskilling and upskilling women workers; encouraging women in STEM (Science, Technology, Engineering and Mathematics); accounting for contextual and cultural complexity; leveraging multi-stakeholder approaches (governments, private sector companies, technical communities and academia); shaping gender stereotypes, and continuing applied research (on how AI systems impact work in general and the working lives of women in particular). You can read the full report here.

The Deloitte report is correct in concluding that “There is still time for organizations to close the gender gap in AI. Organizations that can bring more women into their AI teams can not only bring much-needed gender equality to the field but also bring more value to their business and customers.” That said, if tech, including AI, is mostly about increasing business efficiency, return on investment, consumer satisfaction and, very importantly, societal good, then it’s hard to think how we can achieve all these objectives without including women in the tech and AI story.

(The correct answer is given below)

CUTTING EDGE

IIT researchers develop an algorithm to cut the cost of data management in IoT devices

Researchers from the Indian Institute of Technology (IIT), Jodhpur, IIT Kharagpur and Indian Institute of Information Technology (IIIT), Guwahati, have teamed up to perform research in the area of Internet of Things (IoT). The team has developed architectures and algorithms to enhance data collection and transmission efficiencies associated with IoT devices and applications through a pre-processing framework, CaDGen (context-aware data generation). By filtering the data irrelevant to the running application, the context analysis method could achieve a nearly 35% reduction in the generated data for a moderately dynamic scenario without compromising the data quality. The researchers believe that such an approach can suit various smart environments in a connected living setup that minimizes the cost of data management while providing effective service architecture for end-users.

Adding colour to solar panels

Have you ever wondered why solar panels are deep black? We learnt in school that black surfaces absorb light the most at over 90%, with some variants absorbing 100%. It’s logical to presume, then, that coloured solar panels would be less efficient than those in black. But that may not be the case in the future. Researchers reporting in the American Chemical Society (ACS Nano) said in a 15 August press note that they developed solar panels “that take on colourful hues while producing energy nearly as efficiently as traditional ones”.

Credit: Adapted from ACS NANO 2022

The team went about the task by spraying a thin layer of a material called photonic glass onto the surfaces of solar cells. The glass was made of a thin, disorderly layer of dielectric microscopic zinc sulfide spheres. Although most light could pass through the photonic glass, selective colours were reflected based on the sizes of the spheres. Using this approach, the researchers created solar panels that took on blue, green, and purple hues while only dropping the power generation efficiency from 22.6% to 21.5%. Next, the researchers plan to explore ways to make the colours more saturated and achieve a wider range of colours.

I hope you have a great weekend, and we would love your feedback.