From the course: DJ Patil: Ask Me Anything
What are the pros and cons with AI in HR roles?
From the course: DJ Patil: Ask Me Anything
What are the pros and cons with AI in HR roles?
(upbeat music) - I am super concerned about people, how people approach and use AI and data in recruiting or any type of matching. And that matching is at the college level, of admissions, or thinking about opportunities, skillsets, those type of things. And the reason I'm concerned is because our algorithms are still pretty dumb. They don't have the sophistication, it's still early days, and the data sets, technically we should use a technical term, they suck. Because if you look at who gets into these colleges, or who gets into a certain role, you don't have examples of people who didn't fit the mold. And so it's very overly biased. And we have to be very careful with that because otherwise we say, "Well, who gets to be a VP of Sales? "Oh you have to have an MBA, cause everyone has it," but there's never been a set of people who we've tested who don't have an MBA. So these data sets are biased. And we know this is concretely true because we've seen it where people have tried to use these algorithms and then suddenly the algorithm is doing something that is literally racist. Because these algorithms are black-boxed, it ignores or rejects a name because it's a name of a particular ethnicity, like specifically the African American names. So, we have to be very, very careful there. There's another part of HR where I think we're going to see a great opportunity around these algorithms and that is to find out when we are ... we have bias. And if the machine's like, hey there's actually, you know all you're doing is hiring people that look the same or a certain ... Certain one-dimensional, the algorithms say, hey that's not ... That's not really okay. That's like flagging this for you. I think that's the way we'd like to have machine learning and AI start to show up, is saying like hey, maybe you should consider the following. Another dimension and this was launched in a project called LinkedIn Skills, that moved into Career Explorer, and then LinkedIn Endorsements as well, is this idea of where do skills transfer. And this largely the genesis of this project originated watching my friends come home from Iraq and Afghanistan after service, and not having the ability to say, hey how does my job act ... Or the work I've done translate over. And so, there's this sort of mapping in the world, if you will, of skills. And what we haven't been able to easily do is say you know what this cluster of skills, you may have one of these skills, but you don't realize that your skills actually fit all over here. - [Interviewer] That's very interesting. So it's really using unsupervised machine learning to create these clusters that we never thought some skills would be bundled into. - Right. - [Interviewer] And so you're really defining a brand new space with that. - Right. You know, there was a joke in the early days of the LinkedIn data science team is we had a neurosurgeon on the team And who had given up neurosurgery 'cause he just loved data and problem solving. And so, the motto of the team in the early days was it's not rocket science or brain surgery, but if it was, we'd still have you covered. (upbeat music)
Contents
-
-
-
What were you like as a kid?3m 17s
-
How did your parents influence you?1m 55s
-
How did you navigate college?4m 7s
-
What are some fond memories from grad school?2m 45s
-
How can we foster learning for everyone?5m 9s
-
What's the importance of learning liberal arts?2m 30s
-
What advice do you have for job seekers?3m 23s
-
How did data science come about?4m 8s
-
What does it take to be a data scientist?4m 1s
-
Why is apprenticeship important?3m 41s
-
How can a data scientist influence policy?2m 20s
-
How can I prepare for data science in college?4m 56s
-
How can hackathons benefit me?1m 30s
-
How did you use data in grad school?2m 15s
-
How is data used in the US?3m 55s
-
How is data used worldwide?1m 38s
-
How do you expose holes in cybersecurity?3m 32s
-
How can we educate people about hacking?2m 30s
-
What are the real threats to personal data?4m 6s
-
Should we focus on media headlines?1m 39s
-
How can we educate people about data use?3m 34s
-
How can people fight for data privacy?2m 46s
-
What's the role of the data scientist in 15 years?4m 30s
-
What are you working on currently?3m 31s
-
How can we make data secure?3m 26s
-
How to serve the people with data science?1m 47s
-
What's the difference between wisdom and experience?1m 54s
-
How do you advocate for science?2m 3s
-
What is the role of AI in today's world?2m 54s
-
What's an example of ethical hacking?2m 9s
-
How do you bring data science into the workplace?2m 29s
-
What is the role of AI in human resources and recruiting?3m 3s
-
What are tools every data scientist should own?2m 44s
-
Is there a data science code of ethics?4m 6s
-
What are AI threats in the cybersecurity world?4m 38s
-
How can data scientists better inform the general public?1m 30s
-
How can people participate in data science?2m 31s
-
Why do people fear a machine revolution?2m 18s
-
How can data inform healthcare?1m 31s
-
Why should we democratize data?2m 14s
-
How are you advocating for science?3m 9s
-
Why is the march for science important?3m 42s
-
What is AI?1m 37s
-
What is an example of robust machine learning?4m 31s
-
What is AI's place in healthcare?3m 29s
-
How can AI impact clinical trials?3m 22s
-
How can a data scientist be best leveraged for business?1m 28s
-
What does a data science team need to thrive?2m 56s
-
What are the pros and cons with AI in HR roles?3m 27s
-
What should be in a data scientist's toolbox?3m 23s
-
What makes up a good data science team?2m 3s
-
What new projects are you working on?2m 51s
-
What data science projects are you working on?1m 40s
-
How can AI and machine learning (ML) help cybersecurity?3m 54s
-
How can governments fight back against AI attacks?3m 5s
-
What can the public do to protect against AI attacks?1m 14s
-
What are neural networks (NN)?2m 8s
-
What's the difference between ML and NN?1m 42s
-
Do you have a favorite machine learning technique?1m 7s
-
How does the Internet of Things work?1m 38s
-
What is a connected city?3m 3s
-
What is the fear associated with data?2m 30s
-
How can we address the fear of machines taking jobs?3m 20s
-
What about job loss due to AI?1m 43s
-
What's the reality of bringing back jobs?1m 50s
-
What is a scientific process for data science?2m 46s
-
What is your tip for not getting overwhelmed by big data?1m 40s
-
How do you accept that you're not going to know stuff?2m 38s
-
What is a dynamic range?2m 1s
-
When does data leave holes?3m 8s
-
How important is diversity on a data science team?2m 13s
-
How does data influence people's emotions?4m 15s
-
How do you train yourself to be intellectually curious?2m 20s
-
How do we empower people to foster dialogue?3m 33s
-
What is your philosophy on leadership?2m 56s
-
How can a company retain employees?3m 42s
-
How do you cultivate employee development?3m 18s
-
How do you identify algorithmic biases?2m 46s
-
Can you describe the process of ethical testing?2m 46s
-
How do you feel about machine learning for business decisions?1m 52s
-
Can you talk about your book?4m 10s
-
What are possible solutions for displacement?2m 23s
-
What impact does technology have on the US economy?3m 2s
-
Can you discuss the future of intelligent things?3m 26s
-
What are the current issues with data collection?2m 10s
-
How is technology changing human expectations?1m 7s
-
Wrapping up1m 5s
-