The Future of Work: a Review of Hiring Algorithms and How Companies Can Avoid Unintended Biases and Negative Outcomes

ABOUT THIS EVENT .

 

Part of our deep dive into exploring how predictive technologies are defining and guiding innovation in Human Resources Management, this research overview and strategy call will review compelling, new research on hiring algorithms, Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias, published by Upturn (an organization that specializes in research and advocacy that advances equity and justice in the design, governance, and use of technology).

After our research overview and discussion, Dr. Lorien Pratt will join us via live video to discuss specific strategies and best practices for developing processes and training HR employees on how to implement AI and manage data to get the best desired outcomes and to sharpen decision-making with the algorithms. Attendees will also participate in a Q&A with Dr. Pratt.

The research overview and strategy call with Dr. Pratt will be expertly moderated by James Jeude, former VP and Practice Leader at Cognizant, thought-leader in AI, data innovation, transformation, analytics, P&L, and co-author of seminal research, AI Transparency, Trust, and Personalization.

Artificial Intelligence (AI) and Machine Learning are giving companies powerful new predictive tools to manage Human Resources in extremely effective ways, particularly for recruitment, performance and workforce development, skills assessment, training and upskilling, conflict resolution, and budgeting. But, as organizations increasingly rely on predictive technologies and complex data, it's becoming clear that these same automation tools that benefit the organization can present unique, unprecedented challenges with potentially devastating uninentional consequences. We'll explore this through the lense of the research report and Dr. Pratt's expert insights, guided by moderator, James Jeude.

The Research Report

In an informal group setting, we will review and discuss the research report, Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias:

SUMMARY

The hiring process is a critical gateway to economic opportunity, determining who can access consistent work to support themselves and their families. Employers have long used digital technology to manage their hiring decisions, and now many are turning to new predictive hiring tools to inform each step of their hiring process.

This report explores how predictive tools affect equity throughout the entire hiring process. We explore popular tools that many employers currently use, and offer recommendations for further scrutiny and reflection. We conclude that without active measures to mitigate them, bias will arise in predictive hiring tools by default.

KEY POINTS

--   Hiring is rarely a single decision point, but rather a cumulative series of small decisions.
--   While new hiring tools rarely make affirmative hiring decisions, they often automate rejections.
--   Predictive hiring tools can reflect institutional and systemic biases, and removing sensitive characteristics is not a solution.
--   Nevertheless, vendors’ claim that technology can reduce interpersonal bias should not be ignored.
--   Even before people apply for jobs, predictive technology plays a powerful role in determining who learns of open positions.
--   Hiring tools that assess, score, and rank jobseekers can overstate marginal or unimportant distinctions between similarly qualified candidates.

Additional Relevant Reading

--   Amazon scraps secret AI recruiting tool that showed bias against women (Reuters)
--   A face-scanning algorithm increasingly decides whether you deserve the job (Washington Post)
--   Job Search 2020: AI Is the New Gatekeeper to Your Dream Career (Observer)
--   A.I. is transforming the job interview—and everything after (Fortune)
--   Decision Intelligence In HR: What is it and How to use it? (Tech Funnel)

After our research discussion, Dr. Pratt will join us via live video for a strategy and Q&A session. Attendees are limited to 30 people in person. If you're unable to attend in person, you can still register to participate in the live strategy call with Dr. Pratt.

All registered attendees will receive a 15% discount to register for Dr. Pratt's upcoming course,  Decision Intelligence for Human Resources: Achieving Desired Outcomes with AI and Data.  

ABOUT DR. LORIEN PRATT


Dr. Lorien Pratt
Dr. Lorien Pratt, Chief Scientist & Cofounder, Quantellia, LLC, Author of  Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World (Sept. 2019)

Dr. Lorien Pratt has been delivering machine learning solutions for her clients for over 30 years, including the Human Genome Project, SAP, the Colorado Bureau of Investigation, the US Department of Energy, and the Administrative Office of the US Courts.

Having led the teams that invented Transfer Learning and Decision Intelligence (DI), she is recognized as a leading innovator by the Women Inventors and Innovator’s Project. Pratt also authored dozens of academic papers, has been on multiple program committees for NIPS and NSF, was guest editor for the journals Machine Learning and Connection Science, wrote a chapter in The People Centered Economy, and co-edited the book:Learning to Learn with Sebastian Thrun.

As chief scientist and co-founder of Quantellia, Pratt speaks worldwide today, has given two TEDx talks, appeared as a keynote speaker at MCubed and was featured on public radio’s Marketplace and TechNation. Pratt's most recent book, Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World, was published by Emerald earlier this year.  Pratt’s company also co-sponsors the Responsible AI/DI Summit, and she blogs at www.lorienpratt.com.

Twitter:  @LorienPratt
LinkedIn:  https://www.linkedin.com/in/lorienpratt/
Facebook:  https://www.facebook.com/lorien.pratt

ABOUT JAMES JEUDE

James Jeude started working with Artificial Intelligence and text mining nearly 20 years ago, and is a regular speaker and author with dozens of publications, podcasts, and videos on the subject.  At Cognizant, he and Dr. Jerry Smith authored the seminal paper on AI Transparency, Trust, and Personalization that led to James's work in AI bias, abuse, and public reaction.

He founded Cognizant's strategic business consulting practice for data management and business intelligence, and now through his company SDE Strategies focuses on guiding his clients to win in the data economy.

DOWNLOAD RESEARCH REPORT

Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias by Miranda Bogen and Aaron Rieke, published by Upturn

The hiring process is a critical gateway to economic opportunity, determining who can access consistent work to support themselves and their families. Employers have long used digital technology to manage their hiring decisions, and now many are turning to new predictive hiring tools to inform each step of their hiring process.

This report explores how predictive tools affect equity throughout the entire hiring process. We explore popular tools that many employers currently use, and offer recommendations for further scrutiny and reflection. We conclude that without active measures to mitigate them, bias will arise in predictive hiring tools by default.



REGISTER

Registration limited to 30 people in real life. Lite bites and beverages included.

Refund Policy: Refunds given up to 7 days before the date of the course. No refunds will be given on cancellations made thereafter.

Start Time

6:00 pm

Wednesday, February 12, 2020

Finish Time

8:00 pm

Wednesday, February 12, 2020

Address

Meet in Place, 75 Spring Street, 2nd floor, New York, NY, 10012

Event Participants