AI for Good and our partners are directly involved with tackling discrimination in the workforce with the application of AI and Machine Learning. We see immense potential for AI to bring transparency to labor markets, hiring practices, and encourage companies to embrace diverse and inclusive workforces.
In 2019 the AI for Good Foundation conducted a broad assessment of the public perception of Artificial Intelligence as the ‘Global Perceptions of AI’ survey. The study found that many people are concerned and fearful of AI’s impact and believe their jobs to be at risk.
Our scientific research indicates that there is no empirical evidence of negative impacts on labor markets due to the introduction of AI technologies. In fact, there is evidence for a positive and statistically significant impact on employment and firm growth.
Artificial Intelligence, Firm Growth, and Industry Concentration
By Tania Babina, Anastassia Fedyk, Alex Xi He & James Hodson
Which firms invest in artificial intelligence (AI) technologies, and how do these investments affect individual firms and industries? The paper provides a comprehensive picture of the use of AI technologies and their impact among US firms over the last decade, using a unique combination of job postings and individual-level employment profiles. It also introduces a novel measure of investments in AI technologies based on human capital and document that larger firms with higher sales, markups, and cash holdings tend to invest more in AI.
Addressing workplace discrimination with AI
Women, in particular mothers and minorities, have unequally born the economic weight of Covid-19, including higher unemployment rates than their male counterparts.
Even without a pandemic, minority employees are often held to different standards. There have been countless PSAs and calls to action on the issue but the truth is, bias is human and eradicating its negative effects is hard. That’s where AI and machine learning tools can help even the playing field.
Artificial Intelligence can reduce discrimination and increase equity by analyzing corporate hiring and promotion practices.
The machine-generated results will be used to generate a Public Scorecard, giving you the knowledge and power to support companies that align with your value system. You can also help us create best practices that define “bias” and eliminate discriminatory computer programs.
Further Research and Resources
This report from Deloitte illuminates ways to increase women's representation in AI. Early STEM education shows young women and girls how AI roles can impact their life trajectory. It takes real, active mentorship that’s organic and promotes curiosity. And it’s crucial that women help trailblaze the pathways for girls, build relationships with them early, and help them become AI leaders that organizations can then champion, retain, and promote.
Through a partnership, Predli will work with the impact-led non-profit organization to help them realize a more equitable and sustainable future. This partnership comes at a pivotal moment in history when, more than ever, organizations at all levels are looking to deliver real, equitable, and fair value from their AI investments.
Marta Slepankova discusses with the AI for Good Summer Fellows how discussions regarding Artificial Intelligence and broader technologies almost exclusively exist in English, and do not take into account disability needs. Slepankova shares why future researchers must work towards inclusivity.
In this talk, AI for Good CEO James Hodson discusses the role of AI at the intersection of individuals, jobs, companies, and financial markets. Increasingly, large new data sources are facilitating our understanding of how individuals, teams, companies, governments, and other entities operate, allowing for new types of modeling that can unlock value and accelerate growth.
The AI for Good Foundation had the pleasure to virtually connect with Dr. Anastassia Fedyk, an Assistant Professor of finance at the Haas School of Business at Berkeley, and learn about her research on the role of glass ceilings in U.S. firms and behavioral biases in individual and group decision-making.
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