from the world's big
Want to survive job automation? Don't think like a robot
Here's why coding skills alone won't save you from job automation.
Scott Hartley is a venture capitalist and best-selling author of The Fuzzy and the Techie (Houghton Mifflin Harcourt, 2017), a Financial Times business book of the month, and finalist for the Financial Times and McKinsey & Company's Bracken Bower Prize for an author under 35. He is a keynote speaker on the Liberal Arts in the age of the Algorithm. He has served as a Presidential Innovation Fellow at the White House, a Partner at Mohr Davidow Ventures (MDV), and a Venture Partner at Metamorphic Ventures. Prior to venture capital, Scott worked at Google, Facebook, and Harvard’s Berkman Center for Internet & Society. He has been a contributing author at MIT Press, and has written for publications such as Quartz, The Financial Times, and Foreign Policy, and been featured in USA Today, Harvard Business Review and The Wall Street Journal. He holds three degrees from Stanford and Columbia, has finished six marathon and Ironman 70.3 triathlons. He is a Term Member at the Council on Foreign Relations, and has visited over 70 countries.
Scott Hartley: I think one of the big counterintuitive points that I draw out in the book 'The Fuzzy and the Techie' is this notion that just because you have technology skills doesn’t necessarily make you relevant in tomorrow’s tech-led, data-infused economy. And if you look at the underliers of jobs, there are tasks that make up every different job that we have, and each of our jobs have some subset of tasks that are rote, that are scripted, that are highly routine. These are things that, over time, we can either program robots to do them if they’re manual or we can program machines to do them through machine learning. But there’s always a subset that’s more complicated or more complex that requires collaboration, that requires communication or doing things that are on the frontier of what we haven’t seen before; things that require improvisation. And those are the very skills that require adaptive or flexible learning. And so I think the counterintuitive point is that just because you have rote technical ability you may actually be more susceptible to job automation than someone who has flexible thinking skills. So it’s this false dichotomy between having technical skills being relevant, having soft skills being irrelevant. In fact it’s more the opposite. So when we think about automation it’s necessary that we engage with data, it’s necessary that we learn the fundamentals of technology, that we learn to code, we learn to speak this new language, but I think we can’t forget as well the soft skills that will enable us to weather the changing economy as the machines continue to take more and more rote and scripted tasks away from humans.
So the progress we’ve seen recently with things like deep learning with the DeepMind and AlphaGo and sort of playing the world champion in Go—I mean, these are fundamentally groundbreaking endeavors, I think the really interesting thing is that the artificial intelligence we talk about today is still context dependent; it’s still dependent on being on a board, being within the confines of a set of rules. And so if you think about simple tasks, those are rules-based tasks that may be very easy to automate, we’ve sort of migrated up the funnel where we’re talking about immensely complicated tasks. But I wouldn’t necessarily say that we’ve transgressed into complexity where there’s really something that’s off the board, off the chess board entirely, off the Go board entirely. And so I think when we can move to a realm where we’re not context dependent, to me that’s one of the definitional qualities of when it’s truly perhaps artificial intelligence and not sort of A.I. that’s largely human led or human guided.
So, one of the new technologies that is in the daily media today that we focus on a lot is this prospect of self-driving cars or automated vehicles on the roads. And if you look under the hood of this new technology we realize that some of the biggest challenges we’re facing are those that have to do with mixed-use environments. So for example, when people migrate towards this new form of vehicle there’s not going to be sort of a zero to one change, there’s going to be this mixed environment for a number of years, potentially decades, where we have self-driving cars, perhaps partially automated vehicles included with human-led cars. And so one of the biggest challenges is more of an anthropological challenge of figuring out: how do we get machines to interface with humans in an effective way? So if you actually look at a company like Nissan some of the most important roles that they’re hiring for are PhD anthropologists who are doing sort of ethnographic studies, looking at human communication by gesture or by raising a nod or giving an eyebrow wave. And these are small things that we sort of take for granted as implicit ways that we communicate as humans, but if you’re trying to transcribe that into code and teach an engineering team how to write the computer code for that, that becomes a very difficult challenge between sort of anthropological research and engineering. And I think that this is a perfect example of how we have to bring together both the fuzzy and the techie to really meet and some of the biggest challenges today with self-driving cars.
So in 2014 we were at the height of fear where there had been a study that came out with the Oxford Martin School that looked at how 47 percent of U.S. jobs we’re at high risk of machine automation. This was also the year where Martin Ford’s 'Rise of the Robots' came out and the pendulum swung all the way to fear. And I think, taking a step back, earlier this year the McKinsey Global Institute came out with a study where it looked at 800 occupations and drilled down into those occupations and looked at the constituent tasks that made up each of those jobs, and it found that around five percent of jobs had 100 percent of tasks that were things that could potentially be automated by machines. But the more interesting conclusion was that for roughly 60 percent of jobs only 30 percent of the tasks within those jobs were things that machines could do over time. And so as machines take over the rote, scripted, and routine aspects of jobs—the things that we’ve done many times before, the things for which we have best practices or good practices, things where you may have a note on the wall that says 'do it explicitly this order of operations these ten steps,'—those are the things that we can program machines to do in a fairly easy way over time. There are obviously questions about the use of internal teams and dedicating resources to optimize certain processes versus others. These things aren’t all going to happen overnight. I think there are a lot of management questions that have to do with resource allocation around some of these issues. So technical feasibility is only the first step of automation. I think then there are many more steps that we need to consider.
But I think the interesting conclusion from the McKinsey Global Institute is that for these 30 percent of tasks that may go to machines over time, what this does is it up-skills or levels-up the human, where we now have to focus on the sort of non-routine aspects of our job, the complex aspects. And in this world of complexity where you may be good at one thing and I’m good at something else we actually start task trading more, we actually start working on one thing for one person and one thing for somebody else. And in this environment of increasing task trading there is a guy named David Deming who is an economist at the Harvard Graduate School of Education and Professor Deming talks about how it's actually the soft skills that reduce the friction, reduce the transaction costs when we trade tasks. So in fact when machines are taking over the rote or routine aspects of our jobs and humans are left with this 70 percent of complex or non-routine tasks it’s actually the soft skills that start becoming more and more important.
The conventional wisdom developing in the face of job automation is to skill up: learn how to code, become a member of the rising tech economy. Venture capitalist Scott Hartley, however, thinks that may be counterproductive. "Just because you have rote technical ability, you may actually be more susceptible to job automation than someone who has flexible thinking skills," he says. Retraining yourself in tech-based areas is smart, but the smartest way to survive job automation is to develop your soft skills—like improvisation, relational intelligence, and critical thinking. Believe it or not, those 'softer' assets will rule in the digital age, so play to what makes you human. In time, everything else will be done by a robot. Scott Hartley is the author of The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World.
Join The Daily Show comedian Jordan Klepper and elite improviser Bob Kulhan live at 1 pm ET on Tuesday, July 14!
Gender and sexual minority populations are experiencing rising anxiety and depression rates during the pandemic.
- Anxiety and depression rates are spiking in the LGBTQ+ community, and especially in individuals who hadn't struggled with those issues in the past.
- Overall, depression increased by an average PHQ-9 score of 1.21 and anxiety increased by an average GAD-7 score of 3.11.
- The researchers recommended that health care providers check in with LGBTQ+ patients about stress and screen for mood and anxiety disorders—even among those with no prior history of anxiety or depression.
Study findings<p>For the study, <a href="https://link.springer.com/article/10.1007/s11606-020-05970-4" target="_blank">published in the Journal of General Internal Medicine</a><em>, </em>Flentje and her team evaluated survey responses from nearly 2,300 individuals who identified as being in the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community. Most of the participants were white, while nearly 19 percent identified as a racial or ethnic minority. Multiple genders were represented with cisgender women (27.2 percent) and men (24.6 percent) making up a majority of the participants. Sixty-three percent had been assigned female at birth. For the most part, participants identified their sexual orientations as queer (40.3 percent), gay (36.5 percent), and bisexual (30.3 percent).</p><p>The JGIM study participants were recruited from the 18,000-participant <a href="https://pridestudy.org/" target="_blank">PRIDE Study</a> (Population Research in Identity and Disparities for Equality), which is the first large-scale, long-term national study focusing on American adults who identify as LGBTQ+. It conducts annual questionnaires to understand factors related to health and disease in this population. </p><p>Participants filled out an annual questionnaire (starting in June 2019) and a COVID-19 impact survey this past spring. Flentje noted that on an individual level, some people may not have experienced a big change in anxiety or depression levels, but for others there was. Overall, depression increased by a <a href="https://patient.info/doctor/patient-health-questionnaire-phq-9" target="_blank">PHQ-9 score</a> of 1.21, putting it at 8.31 on average. Anxiety went up by a <a href="https://www.mdcalc.com/gad-7-general-anxiety-disorder-7" target="_blank">GAD-7</a> score of 3.11 to an average of 8.89. Interestingly, the average PHQ-9 scores for those who screened positive for depression at the first 2019 survey decreased by 1.08. Those who screened negative for depression saw their PHQ-9 scores increase by 2.17 on average. As for anxiety, researchers detected no GAD-7 change among the study participants who screened positive for anxiety in the first survey, but did see an overall increase of 3.93 among those who had initially been evaluated as negative for the disorder. </p>
Risks among gender and sexual minorities<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="fc3fd1ae68b77bbbf58a6995638d6d65"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/EnUqDjCqg0A?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>The LGBTQ+ community is a vulnerable population to mental health concerns because of their fear of stigmatization and previous discriminatory experiences.</p> <p>Previous research by the Human Rights Campaign has found "that LGBTQ Americans are more likely than the <a href="https://medicalxpress.com/tags/general+population/" target="_blank">general population</a> to live in poverty and lack access to adequate medical care, paid <a href="https://medicalxpress.com/tags/medical+leave/" target="_blank">medical leave</a>, and basic necessities during the pandemic," said researcher Tari Hanneman, director of the health and aging program at the campaign.</p> <p>"Therefore, it is not surprising to see this increase in anxiety and depression among this population," Hanneman said in the release. "This study highlights the need for <a href="https://medicalxpress.com/tags/health+care+professionals/" target="_blank">health care professionals</a> to support, affirm and provide <a href="https://medicalxpress.com/tags/critical+care/" target="_blank">critical care</a> for the LGBTQ community to manage and maintain their mental health, as well as their physical health, during this pandemic."</p>
What should health care providers do?<p>The authors of the study recommend that health care providers check in with LGBTQ+ patients about stress and screen for mood and anxiety disorders in members of that community—even among those with no prior history of anxiety or depression.</p><p>As cases of COVID-19 continue to mount, the sustained social distancing, potential isolation, economic precariousness, and personal illness, grief, and loss are bound to have increased and varied impacts on mental health. Effective treatments may include individual therapy and medications as well as more large-scale coronavirus support programs like peer-led groups and mindfulness practices. </p><p>"It will be important to find out what happens over time and to identify who is most at risk, so we can be sure to roll out public health interventions to support the mental health of our communities in the best and most effective ways," said Flentje.</p>
What we know about black holes is both fascinating and scary.
- When it comes to black holes, science simultaneously knows so much and so little, which is why they are so fascinating. Focusing on what we do know, this group of astronomers, educators, and physicists share some of the most incredible facts about the powerful and mysterious objects.
- A black hole is so massive that light (and anything else it swallows) can't escape, says Bill Nye. You can't see a black hole, theoretical physicists Michio Kaku and Christophe Galfard explain, because it is too dark. What you can see, however, is the distortion of light around it caused by its extreme gravity.
- Explaining one unsettling concept from astrophysics called spaghettification, astronomer Michelle Thaller says that "If you got close to a black hole there would be tides over your body that small that would rip you apart into basically a strand of spaghetti that would fall down the black hole."
The team caught a glimpse of a process that takes 18,000,000,000,000,000,000,000 years.
- In Italy, a team of scientists is using a highly sophisticated detector to hunt for dark matter.
- The team observed an ultra-rare particle interaction that reveals the half-life of a xenon-124 atom to be 18 sextillion years.
- The half-life of a process is how long it takes for half of the radioactive nuclei present in a sample to decay.
A new study looks at what would happen to human language on a long journey to other star systems.
- A new study proposes that language could change dramatically on long space voyages.
- Spacefaring people might lose the ability to understand the people of Earth.
- This scenario is of particular concern for potential "generation ships".