Перейти к содержанию сайта
The Equality Machine
Book

The Equality Machine

Harnessing Digital Technology for a Brighter, More Inclusive Future

Public Affairs, 2022 подробнее...

Buy the book


Editorial Rating

9

getAbstract Rating

  • Concrete Examples
  • Hot Topic
  • Inspiring

Recommendation

Society has become polarized between those who fear new technologies due to their potential to exacerbate existing inequities and those who naively envision a technological utopia without anticipating risks. Law professor Orly Lobel urges humanity to bridge these divides, working together to create an “equality machine” instead. Lobel calls on stakeholders across sectors to harness the power of AI, machine learning, and big data to reduce inequities, bias, and discrimination. Learn about efforts around the world to create a better future in which humanity uses “technology for good.”

Summary

The emergence of intelligent machines triggers a need to uphold values of equity and fairness.

Over the past decade, discourse about technological change has been largely polarized. Silicon Valley “insiders” — predominantly white men — have viewed “disruption” as their key objective, lauding the potential of new technologies to drive economic growth and create efficiencies. Meanwhile, “outsiders” — such as people of color, women, and those from rural areas and the developing world — have issued warning cries about potential new forms of exclusion and inequities. Thus, two dichotomous visions of the future have emerged: Outsiders worry that new technology will create a dystopian “robopocalypse,” while insiders dream of an innovation utopia.

Humanity must take a middle path between naive optimism and fearful pessimism: cultivating awareness of the ways new technologies can perpetuate inequities while simultaneously taking action to improve the fairness of technological systems. Some have tried to improve machine fairness by removing identity markers, like ...

About the Author

Orly Lobel is the director of the Center for Employment and Labor Policy and the Warren Distinguished Professor of Law at the University of San Diego as well as a tech policy consultant to leading organizations. She is the award-winning author of several books and numerous research articles.


Comment on this summary

More on this topic

Related Skills

Привлекайте и нанимайте персонал
Корпоративные финансы
Развивайте навыки мышления
Цифровая трансформация
Discover AI Use Cases
Discover and Understand Digital Technologies
Будущее работы
Drive AI Transformation
Enable Digital Organization
Высшее руководство
Управление персоналом
Повышайте культурную компетентность
Лидерство
Leverage AI for Leadership
Leverage AI in Your Daily Tasks
Управляйте вознаграждением
Менеджмент
Софт-скиллз
Повышайте цифровую грамотность
Understand AI
Understand Economics
Навыки для работы
Discover AI Use Cases in the Consulting Industry
Leverage AI for Finance
Неравенство
Use AI for Fraud Detection
Discover AI Use Cases in Legal Services
Manage Digital Risk and Ethics
Поддерживайте гендерную инклюзивность
Use AI for Data Analysis
Назначайте справедливое вознаграждение
Discover AI Vendors for HR
Проводите политику DEI
Use AI for General Research
Discover AI Use Cases in the Finance Industry
Leverage AI for Management
Влияние ИТ на этику
Новые технологии для работы
Measure AI Business Impact
Use AI for Skills Matching
Drive AI Adoption in Teams
Leverage AI for Compliance
Understand AI Impact on Work
AI Transformation
Discover AI Use Cases in the Technology Industry
Этично используйте цифровые технологии
Guide Teams Through AI Transition
Оценивайте кандидатов
Understand AI Impact on Business and Economy
Use AI for Workforce Planning
Understand AI Risks
Leverage AI for HR
Разрабатывайте стратегии найма
Предупреждайте когнитивные искажения
Изучите тему неосознанной предвзятости
Use AI for Credit Scoring
Understand AI Societal Impact
Use AI Ethically as a Leader
Нанимайте разнообразные таланты
Use AI for Talent Sourcing
Understand AI Ethical Impact
Use AI for Candidate Screening
Используйте ИИ этично