Kristian Lum's guest appearances

Kristian Lum

Women in Data Science

Origins Podcast with Ryan McGranaghan

ACM ByteCast

Jennifer Widom

Kirk Borne

Ayanna Howard

Robin Murphy

David Heinemeier Hansson

Melanie Mitchell

Elizabeth Anderson

Giorgia Lupi

Nora Bateson

Matt Russo

Janet George

Vint Cerf

John Hennessy

Dave Patterson

Newsha Ajami

OwlTail

Kristian’s interest in statistics and algorithmic fairness has taken her on a winding career path from academia to business, to public service, and back to academia. As she has made different career changes, she didn’t decide between academia vs. industry vs. non-profit, it was more about the problem she was interested in working on at the moment, and what else is happening in her life. After she earned her PhD in Statistical Science from Duke University, she worked as a research professor at Virginia Tech where she did microsimulation and agent-based modelingin a simulation lab. After that, she tried a data visualization and analytics startup called DataPad that was quickly acquired. When she was thinking about her next step in her career, she wanted to do something with social impact.She was fascinated by the work of the Human Rights Data Analysis Group (HRDAG) that was applying statistical models to casualty data to estimate the number of undocumented conflict casualties. She spent a summer working for HRDAG in Colombia and then decided to join the organization full time. She spent five years as HRDAG’s lead statistician leading the group’s project on criminal justice in the United States focused on algorithmic fairness and predictive policing. Predictive policing uses algorithms to help the police decide where to deploy their resources based on crime statistics, so if you look at where crimes are most likely to occur, this is where you police more often. Kristian’s work showed that these algorithms could actually perpetuate historical over-policing and racial bias in minority communities. Early this year, she moved from HRDAG back to academia. She started her new position at the University of Pennsylvania in the Computer and Information Science Department on March 2 and a week later Penn closed down for COVID. Over this year, she has learned that she needs to adjust her expectations for herself, and not be so frustrated when she can't get things done that maybe under normal circumstances she could. It's not just working from home with her daughter nearby, it's the stress of everything that's going on, the additional mental fatigue of having to do all these risks calculations. This year has also made her appreciate the increasingly critical role of data science in driving data-driven decision making.RELATED LINKSConnect with Kristian Lum on LinkedIN and TwitterLearn more about Penn EngineeringLearn more about HRDAGConnect with Margot Gerritsen on Twitter (@margootjeg) and LinkedInFind out more about Margot on her Stanford Profile

Kristian’s interest in statistics and algorithmic fairness has taken her on a winding career path from academia to business, to public service, and back to academia. As she has made different career changes, she didn’t decide between academia vs. industry vs. non-profit, it was more about the problem she was interested in working on at the moment, and what else is happening in her life. After she earned her PhD in Statistical Science from Duke University, she worked as a research professor at Virginia Tech where she did microsimulation and agent-based modelingin a simulation lab. After that, she tried a data visualization and analytics startup called DataPad that was quickly acquired. When she was thinking about her next step in her career, she wanted to do something with social impact.She was fascinated by the work of the Human Rights Data Analysis Group (HRDAG) that was applying statistical models to casualty data to estimate the number of undocumented conflict casualties. She spent a summer working for HRDAG in Colombia and then decided to join the organization full time. She spent five years as HRDAG’s lead statistician leading the group’s project on criminal justice in the United States focused on algorithmic fairness and predictive policing. Predictive policing uses algorithms to help the police decide where to deploy their resources based on crime statistics, so if you look at where crimes are most likely to occur, this is where you police more often. Kristian’s work showed that these algorithms could actually perpetuate historical over-policing and racial bias in minority communities. Early this year, she moved from HRDAG back to academia. She started her new position at the University of Pennsylvania in the Computer and Information Science Department on March 2 and a week later Penn closed down for COVID. Over this year, she has learned that she needs to adjust her expectations for herself, and not be so frustrated when she can't get things done that maybe under normal circumstances she could. It's not just working from home with her daughter nearby, it's the stress of everything that's going on, the additional mental fatigue of having to do all these risks calculations. This year has also made her appreciate the increasingly critical role of data science in driving data-driven decision making.RELATED LINKS Connect with Kristian Lum on <a href="https://www.linkedin.com/in/kristian-lum-01365055/" rel="nofollow" target="_blank">LinkedIN</a> and <a href="https://twitter.com/KLdivergence" rel="nofollow" target="_blank">Twitter</a> Learn more about <a href="https://www.seas.upenn.edu/" rel="nofollow" target="_blank">Penn Engineering</a> Learn more about <a href="https://hrdag.org/" rel="nofollow" target="_blank">HRDAG</a> Connect with Margot Gerritsen on <a href="https://twitter.com/margootjeg" rel="nofollow" target="_blank">Twitter (@margootjeg)</a> and <a href="https://www.linkedin.com/in/margot-gerritsen-2b01084/" rel="nofollow" target="_blank">LinkedIn</a> Find out more about Margot on her <a href="https://profiles.stanford.edu/margot-gerritsen" rel="nofollow" target="_blank">Stanford Profile</a>

Kristian Lum | Applying Statistics to Promote Fairness and Transparency

In this episode of ACM ByteCast, Rashmi Mohan welcomes Kristian Lum to the podcast. Lum is part of the research faculty at the University of Pennsylvania's CIS Department. Previously, she was Lead Statistician at the Human Rights Data Analysis Group (HRDAG), where she led the project on criminal justice in the United States. She's widely known for her work on algorithmic fairness and predictive policing and is a key organizer of the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT).  Lum discusses her transition from math and statistics into computer science, and how her lab work in bioinformatics expanded her interest into social issues. They touch on the sensitive nature of data and privacy and gray areas in criminal justice data collection. Lum mentions some applications of her work, advising the NYC Mayor's Office of Criminal Justice and partnering with the ACLU. She also describes a very timely project accounting for the time lag between COVID-19 infection and death. Finally, she traces her winding, fascinating career path from academic to industry and back.

In this episode of ACM ByteCast, Rashmi Mohan welcomes Kristian Lum to the podcast. Lum is part of the research faculty at the University of Pennsylvania's CIS Department. Previously, she was Lead Statistician at the Human Rights Data Analysis Group (HRDAG), where she led the project on criminal justice in the United States. She's widely known for her work on algorithmic fairness and predictive policing and is a key organizer of the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT). Lum discusses her transition from math and statistics into computer science, and how her lab work in bioinformatics expanded her interest into social issues. They touch on the sensitive nature of data and privacy and gray areas in criminal justice data collection. Lum mentions some applications of her work, advising the NYC Mayor's Office of Criminal Justice and partnering with the ACLU. She also describes a very timely project accounting for the time lag between COVID-19 infection and death. Finally, she traces her winding, fascinating career path from academic to industry and back.

Kristian Lum - Episode 4

Show Notes: Human Rights Data Analysis Group (HRDAG) (1:40) The contagious nature of imprisonment paper (1:50) Value of community colleges (6:30) Professor Dan Balaguy at Sierra College (7:20) Professor Richard Stong at Rice University - Combinatorics (8:30)  Coming to an understanding of one’s career and curiosity (10:20)  How can we make the public more data literate (i.e., numeracy)? (12:15) Maintain a healthy skepticism of numbers - think more critically (see Seth Godin’s thoughts)  Data can encode discrimination and bias (16:10) Predictive policing algorithms - Kristian’s paperBe reflective about where patterns in data come from Importance of uncertainty (20:00) HRDAG ‘casualty estimations’ (21:10) Humanize the data (22:00) Describing how systematic things can be (23:50) Taking chances (e.g., Tim Ferriss guidance on cold emailing) (24:50) Where do you get your confidence and energy (26:50) Maintaining beginner’s mindset - blur disciplinary lines (28:20) “The most beautiful experience we have is the mysterious” -Einstein (29:20) How do you grapple with the outrage of injustice? Those with data skills need to get involved with criminal justice reform (36:20) Volunteer with public defenders - make sure you are a low barrier to people if you volunteer Talk with the people closest to the problem - human-centered approachFind ways that your unique skills can help How do you maintain your energy? (39:50) Morning routine (40:30) Lightning Round (43:10) Book: Harry Potter Passion: sowing costumes What is making your heart sing now? Her daughter Screwed up: partial differential equations Further reading and getting involved in criminal justice reform Pod Save the People podcast (38:30) https://theappeal.org/ news source (39:00) Ear Hustle podcast Organizations leading the way  Were to find Kristian online: Twitter: @KLdivergence (https://twitter.com/KLdivergence) 'Five-Cut Fridays’ series  Kristian’s list

Show Notes: <ul><li><a href="https://hrdag.org/" rel="nofollow" target="_blank">Human Rights Data Analysis Group (HRDAG)</a> (1:40) </li><li><a href="https://royalsocietypublishing.org/doi/full/10.1098/rsif.2014.0409" rel="nofollow" target="_blank">The contagious nature of imprisonment</a> paper (1:50) </li><li>Value of community colleges (6:30) </li><li><a href="https://www.sierracollege.edu/directory/groups/academics/science-math/math/daniel-balaguy.php" rel="nofollow" target="_blank">Professor Dan Balaguy at Sierra College</a> (7:20) </li><li><a href="https://www.genealogy.math.ndsu.nodak.edu/id.php?id=30952" rel="nofollow" target="_blank">Professor Richard Stong at Rice University</a> - <a href="https://mathworld.wolfram.com/Combinatorics.html" rel="nofollow" target="_blank">Combinatorics</a> (8:30)  </li><li>Coming to an understanding of one’s career and curiosity (10:20)  </li><li>How can we make the public more data literate (i.e., <a href="https://en.wikipedia.org/wiki/Numeracy" rel="nofollow" target="_blank">numeracy</a>)? (12:15) <ul><li>Maintain a healthy skepticism of numbers - think more critically (see <a href="https://seths.blog/2017/02/nextstep/" rel="nofollow" target="_blank">Seth Godin’s thoughts</a>)  </li></ul></li><li>Data can encode discrimination and bias (16:10) <ul><li><a href="https://www.brennancenter.org/our-work/research-reports/predictive-policing-explained" rel="nofollow" target="_blank">Predictive policing algorithms</a> - <a href="https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-9713.2016.00960.x" rel="nofollow" target="_blank">Kristian’s paper</a></li><li>Be reflective about where patterns in data come from </li></ul></li><li><a href="https://berkeleysciencereview.com/2014/04/importance-uncertainty/" rel="nofollow" target="_blank">Importance of uncertainty</a> (20:00) </li><li>HRDAG ‘<a href="https://hrdag.org/2013/06/13/counting-casualties-in-syria/" rel="nofollow" target="_blank">casualty estimations</a>’ (21:10) <ul><li>Humanize the data (22:00) </li></ul></li><li>Describing how systematic things can be (23:50) </li><li>Taking chances (e.g., <a href="https://www.entrepreneur.com/article/314465" rel="nofollow" target="_blank">Tim Ferriss guidance on cold emailing</a>) (24:50) </li><li>Where do you get your confidence and energy (26:50) </li><li>Maintaining beginner’s mindset - blur disciplinary lines (28:20) </li><li>“The most beautiful experience we have is the mysterious” -Einstein (29:20) </li><li>How do you grapple with the outrage of injustice? </li><li>Those with data skills need to get involved with criminal justice reform (36:20) <ul><li>Volunteer with public defenders - make sure you are a low barrier to people if you volunteer </li><li>Talk with the people closest to the problem - <a href="https://medium.com/dc-design/5-key-lessons-for-criminal-justice-reform-113b31057a5a" rel="nofollow" target="_blank">human-centered approach</a></li><li>Find ways that your unique skills can help </li></ul></li><li>How do you maintain your energy? (39:50) </li><li>Morning routine (40:30) </li><li>Lightning Round (43:10) <ul><li>Book: Harry Potter </li><li>Passion: sowing costumes </li><li>What is making your heart sing now? Her daughter </li><li>Screwed up: partial differential equations </li></ul></li><li>Further reading and getting involved in criminal justice reform <ul><li><a href="https://crooked.com/podcast-series/pod-save-the-people/" rel="nofollow" target="_blank">Pod Save the People</a> podcast (38:30) </li><li><a href="https://theappeal.org/" rel="nofollow" target="_blank">https://theappeal.org/</a> news source (39:00) </li><li><a href="https://www.earhustlesq.com/" rel="nofollow" target="_blank">Ear Hustle</a> podcast </li><li><a href="https://centerforprisonreform.org/prison-reform-organizations/" rel="nofollow" target="_blank">Organizations</a> leading the way  </li></ul></li><li>Were to find Kristian online: <ul><li>Twitter: @KLdivergence (<a href="https://twitter.com/KLdivergence" rel="nofollow" target="_blank">https://twitter.com/KLdivergence</a>) </li></ul></li><li>'<a href="http://ryanmcgranaghan.com/five-cut-fridays-col.html" rel="nofollow" target="_blank">Five-Cut Fridays</a>’ series  <ul><li><a href="https://open.spotify.com/playlist/21lbFORXNEztA5E6EvNeTA?si=JYTFzKbLROiuLxt93Kv88w" rel="nofollow" target="_blank">Kristian’s list</a></li></ul></li></ul>

Episode 19: Kristian Lum - Lifelong curiosity and Criminal Justice Reform through data