Is artificial going to displace humans? I hear this concern a lot and this article in Mother Jones does a good job articulating the reality of robot colleagues.
I realize now that a lot of these projections about the rapid acceleration of computer learning rely on Moore’s Law – the historically-true law that computing power (in the original case, transistors) double about every two years). However, Moore’s Law may eventually break down, and outcomes of advancement don’t always match our expectation. For instance, the rise of the computer age led many to assume that paper would soon be phased out… yet we are using more of it than ever.
The most interesting section of this article was the markers we should look for if AI really is taking our jobs:
A steady decline in the share of the population that’s employed
Fewer job openings than in the past
Middle-class incomes flatten in a race to the bottom
Corporations stockpile more cash and invest less in new products and factories
Labor’s share of national income decline and capital’s share rise
And… hmm. A few markers there but 2019 is looking a bit better than 2013 when this article was published.
Kicking off this month with a primer on AI from waitbutwhy.com. This is from 2015, so there have probably been leaps in AI since this was written, but it is helpful as an anchor.
There are three types of AI:
Artificial Narrow Intelligence: We’re here now. AI that can reliably deliver better outcomes than a human brain, such as navigating with a map on your phone and getting customized music recommendations.
Artificial General Intelligence: This is AI that can reason and solve problems. We’re not here yet.
Artificial Superintelligence: This is intelligence that greatly exceeds human intelligence across all spectrums. This could be closer than we think.
This primer on AI goes into a lot of detail on the exponential increase of computing power over time as well.
When I think about AI’s applications for recruiting and HR, I think of many areas that artificial narrow intelligence is just starting to be applied. Recommendations based on past choices can be generated with existing data. And I also see the potential for recreating bias; this comes up over and over again as a concern with AI for recruiting. I’m curious to read more about how that can be addressed.
Having touched companies’ recruiting processes in some capacity the entirety of my career, I’ve been fascinated with the ways recruiting has evolved in that time. As a snapshot of this change, ten years ago as a new recruiter, I sometimes called an advertising agency to help post retail openings in the local newspaper. Today in recruiting operations, we use Google Analytics and tracking pixels to see performance of online postings, and programmatic advertising can automate some placement decisions.
One of the most exciting advancements in the field is artificial intelligence. Already there are HR tech startups touting their use of AI to enhance and improve the recruiting experience. The tagline is generally something about removing human bias and increasing efficiency – great arguments to move towards technology!
As a data analyst and a former recruiter, I am both excited and skeptical. Can these tools do what they promise? Do they truly apply AI or is this advanced statistics dressed up? And finally – aren’t people a critical component of the hiring practice?
To dive into some of these questions and familiarize myself with the state of AI, I’ve decided to commit my February to learning more about it. Every day throughout February, I will learn something about artificial intelligence and share it here. I’m focused on the following areas:
Defining artificial intelligence. What counts as artificial intelligence? What is the difference between AI and machine learning or are they interchangeable?
What’s the state of artificial intelligence in recruiting? Who is already doing this and how successful is it?
What are the promises and pitfalls of AI?
I realize that these three areas are rich enough that I could probably devote a month (or more!) to each. My intention here is to more broadly explore, though, so I’ll touch on all of these in one short month.
I’m looking forward to this month of learning and hope you follow along! Feel free to share any interesting tidbits, resources or your own interest with me here or via email or Twitter. Here’s to learning!
Summer is here and I’m enjoying the long hot days! Here’s what I’m into this month:
College reunion. It was fun to go back to Dickinson College this month and stay in the dorms with friends. It’s funny how a trip back to school can make it feel like no time has passed at all…
Exploring Queens. I moved to this borough almost a year ago and made a long list of places to check out. I’m slowly making my way through and finding so many great places. I visited MoMA PS1, Brooklyn Boulders Queensbridge and Citifield (thought not for the first time). I’m taking a guitar class at Queens Guitar School and after class, I’ll meet Pete to try a new restaurant in the neighborhood (Astoria). We really like Milkflower and Snowdonia.
Chris Guillebeau’s Side Hustle School. I love a good project and this one from Chris Guillebeau is very compelling. He’s releasing a new podcast every day in 2017 about people and their side hustles. I really love how short each one is (most are <10 minutes) and that he includes quantitative measures of success, like revenue! I’m conflicted about the push for millennials to start a side hustle (more on that another time), but I appreciate this content.
The Getting Things Done method from David Allen and reaching Inbox Zero. I’ve heard about this on life hack sites for years and I’m finally reading the book. I haven’t fully committed, but there are great tips for leading a more minimal and organized life.
Long walks. I’m trying to get 10,000 steps a day, something that’s disturbingly difficult with an office job. Now that the weather’s nice I try to walk home across Queensboro Bridge or take a walk along the waterfront if I have time after dinner. Not always possible, but great when it happens.
Afterward a whirlwind of travel in March, I’m enjoying a more home-bound April.
Lots of family time! My cousin is getting married in Pennsylvania at the end of the month, and it’s a great reason to get together with the Laffertys. I had fun exploring Philadelphia for her bachelorette party this weekend, and brunch at Harp & Crown was a perfect wrap-up. This has led to more plans for family get-togethers in 2017, like seeing Classic East in July!
So much music. The month kicked off with a house concert hosted by a friend and I went to Blue Note to see jazz when Autumn was in town over Easter weekend. After a six-week hiatus, I’m back to guitar lessons. I’m learning Don’t Think Twice by Bob Dylan and Diamonds and Rust by Joan Baez.
Continuing with the music theme, I will finally finish my listen of the first 50 albums on the 500 Greatest Albums of All Time list from The Rolling Stone. I got James Brown’s ‘Live at the Apollo’ at the library this weekend since I couldn’t find it in full on any of my typical online music sources.
Starting – but not finishing – lots of books. If I complete the books I’m currently reading, I’ll exceed my reading goal for the year. I’m reading tons of founder bios lately and really enjoying them.
In the meantime, I’m also working on some longer-term projects that will hopefully come to fruition in the next 3-5 months. Good start to the year!
I’m breaking my posting hiatus with some of the stuff I’m following this month.
Lots of travel. So many of my trips strangely converged this month. Spain, Houston and Scottsdale. I checked off two bucket list items this month – visiting the Alhambra and the Johnson Space Center!
Outer space and life coming full circle. In 2009, I went to Scottsdale to recruit for the new Barneys New York store (unfortunately now closed). While there, Buzz Aldrin was signing his new book, Magnificent Desolation, at the Louis Vuitton store in the mall. The book was a very special Christmas gift to my dad that year. This winter, while going through my mom’s bookshelves as she prepares to sell my childhood home, I found Buzz’s book. I brought it back to Scottsdale to read poolside this month. Having also seen the Saturn V rocket at the Johnson Space Center just a week before, I felt like a real superfan.
So much reading. I finally finished Dubliners this month and Goodreads is moving up as one of my favorite social media accounts.
Getting back to writing in some small ways. More to come soon.
Career advice from powerful women. First Ann Shoket‘s new book The Big Life and now Sallie Krawcheck’s Own It. It’s exciting to hear how they navigated their careers and the advice they have for women like me. I saw Krawcheck speak at Work-bench last week and she was riveting. She came across as very authentic and direct, and it was great to speak with her briefly as she signed my book.
I am fascinated with people’s career paths and have spent much of my own career focused on why people choose jobs, both as a recruiter and as a data analyst. That’s why I loved hearing this episode about finding meaning at work on The Hidden Brain.
This episode is an interview with Amy Wrzesniewski, a psychologist at Yale University. She says that people can be divided into three groups when it comes their approach to their job: they see it as a “job,” a “career” or a “calling.” People equally split into these groups regardless of position. Those who see their job as a calling report the greatest satisfaction. To see which group you fall into, take the quiz here.
I find this so interesting because a lot of mainstream career advice is to follow your passion. That’s so vague, and in my opinion, so wrongheaded (see Cal Newport’s brilliant take on this). It’s difficult to identify a passion at the start of a career.
As I daydream about the coming summer, I’ve been reading and listening to a lot of stories about outdoor adventures and getting away from it all to find yourself. It’s a romantic idea, but you don’t need to leave it all behind to discover your passion or find joy in the work you do. You may just need to understand your orientation towards work. (Though unfortunately, this makes for less compelling stories of self-actualization.)
This afternoon I’m returning to Columbia Business School to speak to the Economics of Organizational Strategy class about business analytics in the HR space. I’m excited to be back at my alma mater to talk about my work. For this class, the professor assigned The Discipline of Business Experimentation from the Harvard Business Review. From the summary:
The data you already have can’t tell you how customers will react to innovations. To discover if a truly novel concept will succeed, you must subject it to a rigorous experiment. In most companies, tests do not adhere to scientific and statistical principles. As a result, managers often end up interpreting statistical noise as causation—and making bad decisions.
YES. All the buzz about big data and analytics fails to mention that if you are not testing correctly, your data may be driving you to make bad decisions! With businesses ramping up analytics capabilities in a big way, I think this happens much, much more than companies are willing to admit.
The example in the HBR article is about Cracker Barrel testing a switch from incandescent to LED lighting at its restaurants. At restaurants that installed the LED lights, traffic decreased. This would initially suggest that LEDs are bad for business. However, by digging deeper, executives realized that the LED lighting made the entrances look dimmer and customers turned away thinking the restaurant was closed. The LED lighting should have been brighter than the incandescent lighting, but individual store managers were going around the corporate lighting standards to install more incandescent lighting, thus making the store look brighter and more welcoming. Therefore, once these stores adhered to the new LED policy, they had fewer lights and were less luminous.
With all the attention around the tools and methods available with statistical analysis, I’m afraid this deeper digging may get short shrift.
It’s important that business professional not only dedicate more time to digging than analysis, but that we can speak the language of data and statistics. With so much more data available to businesses today, knowing how to use it for decision-making is a competitive advantage.
I’m fresh off what was probably my 20th+ family trip to Walt Disney World, and as always it was such a magical time. After so many visits, it’s fun to experience the parks with a first-timer. and this time it was my sister’s boyfriend, Frank.
The Carousel of Progress sparked a great lunchtime discussion about what technology will look like at the end of this century. The Carousel of Progress is an animatronic stage show that shows an American family at four points in the 20th century, highlighting technology innovations in the home. It kicks off at the turn of the century, showing electric lights and cast iron stoves, and the “future” scene takes places in the 1990s, highlighting virtual reality games, self-flushing toilets and voice-activated appliances. After the ride, we all dreamed up what a 2000s Carousel of Progress would contain. Here in 2016 we’d be the very first scene of the show.
We didn’t have to stretch too far to imagine what that scene would contain – we were wearing it. Disney World has integrated wearable technology into its parks with the Magic Bands. We all had a Magic Band in a chosen color with our name printed on the inside and used it as our hotel key, our park ticket, our credit card… It was everything. Meanwhile, all my ride photos popped up immediately in my Disney mobile app, presumably linked through my Magic Band.
Working in analytics, I am curious about the other side of the Band – the big data side. I would love to get a glimpse at what the data scientists at Disney are conjuring up with all the movement and spending data they get through the Magic Bands. Disney has spent over $1 billion on the MyMagic+ program so it’s clear they have big plans for ROI. So far reception has been positive, and the overall creepy factor I felt when my face first magically appeared on my Disney app – screaming on the new Seven Dwarves Mine attraction – was quickly replaced by joy when watching the two-minute video of my family’s reactions at various points on the new ride. From Wired:
No matter how often we say we’re creeped out by technology, we tend to acclimate quickly if it delivers what we want before we want it.
Just like the Carousel of Progress, technological innovation moves fast, and even now Magic Bands are moving to the past. The next scene takes place in Shanghai Disney, where everything will happen seamlessly through a smartphone. I’m adding Shanghai Disney to the bucket list!