People say that change is a constant.
But change isn’t constant.
Organizations and industries can be disrupted in just one day. Now more than ever, leaders have to look to the future if they’re going to lead it. They have to be prepared for what’s coming to protect what’s already here. They have to predict disruption today for stronger impact tomorrow, because the future belongs to us all.
In this episode of B2B Tech Talk, Keri Roberts catches up with Matthew Griffin
, an international advisor at 311 Institute
and Wells Future Forum and speaker on the Future of Technology
, to discuss the future of work.
Matt also explains:
- Why he got into his role of thinking and teaching 20-50 years ahead
- What Industry 4.0 is and what it looks like in terms of time frame
- How automated and autonomous platforms fit into the future of work
- What artificial intelligence means for employees, organizations and society
Looking to the future
Stakeholders around the world require a different type of view of the future depending on the seat they sit in.
A global multinational might care about what happens this year or next year, maybe even five years out. But a sovereign government’s point of view generally starts about 20-50 years out, particularly as they’re starting to plan large infrastructure projects relating to things like transportation, energy, future of education, etc.
With the right foresight and adaptability, the world can be changed at amazing speed. Consider the current pandemic: traditionally, it would take 10 years to create a vaccine. But when you take a sense of urgency and combine it with human ingenuity and exponential technologies like AI, machine learning, gene editing, etc. … all of a sudden, we’ve now realized three vaccines being created in 10 months.
What is Industry 4.0?
The Fourth Industrial Revolution, also known as Industry 4.0, is right around the corner. Broadly speaking, Industry 4.0 is the use of intelligence to help creators produce new things in new ways.
Industry 4.0 is already emerging around the world, particularly in the manufacturing sector. Because of a combination of robotics with machine vision, fully autonomous (also known as “dark manufacturing”) facilities are on the rise and spreading. This next industrial revolution will usher in fully autonomous platforms and systems that manage, operate and scale themselves.
Automated vs. autonomous platforms
Both automated and autonomous platforms have a significant impact on the future of work, but there’s a massive difference between the two.
When organizations that perform digital transformation talk about the concept of robotic process automation
, they’re referring to a strategy that takes manual tasks and automates them for a more efficient workflow. The problem is, this is a relatively inept tactical system.
On the other hand, autonomous
platforms are able to broker and manage transactions independent of humans. They aren’t just automating the process; they’re intelligent. Creative machines (AI that can innovate, design and produce) work very closely to how humans work.
Democratizing access to expertise
Much of mainstream media talks up the risk automation poses to jobs.
Just look at Amazon. They already have a full suite of fully autonomous technologies that would allow them to automate the vast majority of their warehouse staff.
But technology reduces the cost of doing something and improves access to doing another more productive thing. Consider Google. Fifty years ago, you would have to go to the library for information. Today, you can get that same information in a matter of seconds.
AI downsizes roles…but a bigger conversation revolves around what happens when we democratize access to expertise. The fact of the matter is that AI is here and it will continue to progress. If that’s the case, the question becomes not “when will it get here?” but “what will I do when it does?”
Everyone will have access to these same tools eventually; the human differentiation is our own intelligence and creativity, and our approach to executing and selling.
Responding to the rise of AI
With the rise of AI, company executives have now got two choices.
Let’s use the example of warehousing: executives can either automate their warehouse people and make them redundant, or they can run a dark warehouse with no humans involved.
In the latter case, rather than make people redundant, those executives could train those same people for new necessitated roles such as looking after the incoming robots. Humans are incredibly adaptable by default and have great capacity to learn new things.
AI may make jobs redundant, but it can’t make humans redundant. If executives know a particular career is going to dead-end and are able to see what future jobs are coming along with AI (i.e., robotics engineers and maintenance staff) they can take that warehouse staff, train them and seamlessly transition them into their new roles.