Five Forces Shaping the Future of Work

How AI automation and human-computer collaboration are changing the workplace.

6 min readMay 25, 2018

“How will this affect jobs?”

This question seems to pop up at almost every AI meetup, talk, or conversation I’m part of. And for good reason. The future of work profoundly affects people’s lives. Yet, there are so many unknowns surrounding it.

I’ve been pondering this and other AI ethics topics for a while. I used to co-organize a meetup exploring the changing role of design in an AI world. And, a couple months ago, I joined Element AI as Solutions Designer to help build commercial applications of human-centred AI. I’m learning a ton — so I’m writing and reflecting as much as possible along the way. Thus this post.

When it comes to work and the workplace of the future, I’ve noticed a number of forces at play. Here are the top 5 forces I’ve been thinking about lately.

1. Talent Pipeline — career development gaps.

Malcolm Gladwell talks about the *10,000 hour rule in his book Outliers, that you need 10,000 hours of practice in order to master a skill. But how can you earn your 10,000 hours if a machine automates a chunk of those practice hours for you?

Take the example of lawyers. In order to become a Senior Parter at a Law Firm, you must first be a Junior Lawyer and work your way up. And, Junior Lawyers gain experience and skills in the early years of their career by performing a lot of repetitive tasks — things like researching registries or extracting data from documents. But many of these tasks usually reserved for Junior Lawyers can now be automated with AI. So therein lies the challenge.

If skill-building tasks are completed by machines instead of humans, how will lawyers straight-out-of-school build the skills necessary to make the leap to more senior positions? The legal profession is not alone in facing this challenge. It will be interesting to see what innovative training, coaching and apprenticeship models emerge to meet these up-skilling needs.

*Note: the validity of the 10,000 hour rule is contentious among academics — but the idea is useful in illustrating this point.

2. Social Contract — renewing trust between employers and employees.

In places like Japan and Sweden, no one seems worried about losing their jobs to robots. Rather, workers in these countries welcome advanced technologies and AI automation, seeing it as a way to improve their productivity, skills, and the company’s competitive advantage, which in turn strengthens their own job security.

Why so chill? It comes down to trust. Trust that, if roles within a company are automated, the company sees it as their responsibility to retrain workers for new roles. Trust that, if the company goes bankrupt, the government has strong social policies (such as healthcare, education, pensions, welfare) to help people get back on their feet.

In Japan, this trust stems from the postwar Lifetime Employment system, which is still alive and well today. It works pretty much how it sounds. You are hired fresh out of college into a large company and work at this same company for your entire life until retirement. If you’re not thriving in a certain role, they will move you to another department and retrain you. If the company is losing money and needs to downsize, it will sell unused machinery and have you tend a vegetable garden in the space where machinery used to be (true story). In turn, employees trust their employers and welcome new innovation and technology. In Sweden, you see a similar culture of trust in employers, strong social safety nets, and openness to new technology.

These two countries offer interesting models to learn from and copy. What can Canadian companies do to renew the social contract between employers and employees? And what is the role of unions to support the strengthening of this social contract?

3. Conditional Basic Income — pay people to study.

In response to job displacement brought on by automation, many (including Elon Musk and Andrew Yang) are pointing to Universal Basic Income (UBI) as a promising solution. UBI is where the government provides a monthly no-strings-attached top-up to a person’s bank account if their income is below a certain threshold. However, UBI has its own challenges. For example, “work” is a way of contributing to society and is tied to a person’s sense of purpose, sense of dignity, and mental wellbeing. So, while UBI might help with paying for basic needs like food and shelter, UBI does not directly support people to get back into the workforce.

That’s why Conditional Basic income (CBI) has been gaining popularity among tech leaders, like Andrew Ng. CBI builds on the spirit of UBI in that it provides financial support to displaced workers. However, CBI differs in that it adds the stipulation that, in order to receive the funds, recipients must be participating in re-skilling and re-training efforts (Note: CBI can take on many forms. The conditions can vary. This paid-to-study version is what people in the AI community are getting excited about lately). CBI offers a way for people to develop new skills, discover new ways to meaningfully contribute to society, and get back to working and to paying the taxes that help this system keep working.

4. Jobs of the Future — soft skills FTW.

Drone Traffic Optimizer, Vertical Farmer, Data Wrangler, Feedback Looper… no one knows what the hot jobs of the future will be. What we do know is that “soft skills” will become more and more important in the workplace, as they are the skills that are the hardest to replicate by a machine. Soft skills are those skills that require emotional intelligence, like inter-personal communication, empathy, conflict resolution, negotiation, and decision making.

Great, so how do we sharpen our soft skills? Practicing having a growth mindset is one way. Playing this awesome game is another (it’s legit, I have it at home and have gifted it to several people). Other ways include practicing giving and receiving feedback thoughtfully and kindly. I’m curious how others practice building their emotional intelligence, please do share in the comments below.

**5. Aging Population—accessible AI tools for all users**

Baby Boomers are retiring. We know this and are adjusting to this exodus from the workforce. We’re also seeing Boomers delay their retirement — for social, financial or other reasons. Comfort with tech is not tied to a person’s age, but learning to use new interfaces and technical tools can be more challenging for non-digital natives. This can be especially true if an older worker has a physical disability or impairment.

As AI tools become ubiquitous across workplaces, embracing Accessible Design principles will ensure that these tools are usable by all users, including older workers and workers with disabilities or temporary impairments. I’m here for that.

You may be thinking “Accessible Design is a no-brainer, why include it here?” Well, some designers are resistant to accessibility principles, fearing that it will make their work ugly or boring. So, there is still a ways to go in making Accessible Design the norm. But, it’s definitely the future.