In honor of International Women’s Day, we’ve taken over the hello, Human Podcast. The special Women in AI series features eight diverse women discussing the intersections of AI and career.
What is the Women in AI series?
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"Women in AI" Teaser
The Business Side of Women in Technology
Senior Director, Global Data & AI COE Lead at Avanade
Some estimates put the number of unfilled tech jobs at more than one million, yet women hold fewer than 25% of all technology jobs. There are several reasons women are under-represented in the sector: gender bias, a lack of information about the potential for STEM careers early in a girl’s education, a shortage of female mentors, company cultures that don’t adequately support women technologists, and more. However, the bottom line is that not enough women are pursuing careers in tech. Fortunately, times are changing. Some companies are taking steps to attract more women employees by addressing pay gaps, offering flexible work policies, and implementing programs to help women thrive.
AI Governance and Ethics Leader at MassMutual Life Insurance
The next generation of AI-powered products and services has the potential to transform every aspect of the health sector. From accelerated drug discovery through biophysical modeling to improved diagnostic accuracy in medical imaging to smart claims management with self-learning software, no corner of the $10 trillion global health industry will remain untouched. Someday consumer-facing apps may become so advanced that they are able to provide affordable healthcare services to billions of people globally with limited access to traditional services. But these advances do not come without risks, as biases in AI raise ethical concerns and present health risks to patients and financial risks to providers and payors.
From Fortune 500 stalwarts to Silicon Valley startups, gender equity has been a challenge for generations. But today despite universal agreement that a fix is overdue, not much has been done to actually move the needle. Because the workplace was not designed to value women, we need to change the ways we make decisions and evaluate talent to truly address the problem, and technology can be an accelerator. Using AI and natural language processing, software can identify bias in performance evaluations and point organizations toward making better decisions about promotions and new opportunities for employees. It’s more than just an issue of fairness for companies to act. For every 10% increase in gender equity toward parity, there is a 1% to 2% increase in revenue.
Developing a high-impact network is a critical factor in long-term professional success and even more important in today’s hyper-connected world. Networking success requires equal parts of will and skill. Contrary to popular opinion, an outsized personality is not a requirement. With practice and persistence, anyone can build and benefit from a high-impact network. Smart Tribe is a company that understands the value of a network and has a developed to AI-enabled platform to connect academia and industry to help address one another’s crucial problems while breaking down silos.
Master of Advanced Management Student at Yale University
Former Director, AI & Marketing Lead at Emergents at Weild & Co.
In the fast paced world of technology, there are various ways to leverage AI and technology for the social good. Yet, it is critical to address the misconceptions and challenges in AI when doing so. Conquering the challenges created by AI, as well as learning how to use those challenges as a motivator can create strong passion for CSR and social justice initiatives. At the end of the day, visibility and awareness of these issues, and how to address this is how we can use technology and AI for the greater good.
Global Diversity and Inclusion Lead – Research and Artificial Intelligence at Google
For leaders, the promise of AI needs to be offset by an understanding of the risks. A lack of diversity and the inherent bias in technology influences many critical decisions around health, education, the workplace and society in general. It’s not the fundamental technology that’s racist or sexist, but the data on which we train the algorithms or the unconscious biases and prejudices of the developers. Battling these biases within and beyond the workplace includes addressing workplace equity and essential diversity and inclusion programs and initiatives. Beyond the world of HR and technology, one path to battling biases involves building awareness at a young age or through professional mentorship.