Last week, I presented on the future of sports at a fund raiser for the Rutgers University Women’s Soccer team. A local Article on the topic captured the high-level themes, but for those interested, here is the full presentation along with two very good reports I tapped into from Delaware North on the future of sports: The Future of Sports 2016 Report and The Future of Sports 2015 Report.
In his twelfth post in the series, Marshall Kirkpatrick focuses on the intersection between artificial intelligence and robotics. By way of reminder, Marshall launched a 30 day series that explores the intersection between AI and the various innovation components on my emerging futures visual.
Here is the summary of a recent article I wrote for the Insurance Innovation Reporter. Please visit their site to see the full Article.
Accelerating advancements in science and technology have set the foundation for massive shifts in the decades ahead, yet we continue to operate on a platform meant for a different time. This platform has hit a productivity wall, and a new emerging platform has changed the expectations of those we engage with. As they advance, these shifts will challenge our long held beliefs and intuition, while changing long standing business models across industries. In the face of this, organizations must unlearn what they know and embrace new ways of thinking. This is especially important in our approach to the workforce and the evolution of our management paradigm. How we lead the modern workforce will require change, and it starts with four crucial shifts: embrace a new way of working, move towards a collaborative management paradigm, value human characteristics, and plug into the emerging platform.
If we are to Think about the Future in a way that helps us thrive in that future, we must excel at connecting dots. I developed the Future Scenarios visual in an attempt to help visualize the dots, as well as the various intersections that amplify the impact of those dots. In parallel with this scenario view, I have looked at various aspects of social change that both influence and impact these scenarios – and vice versa – but until now, those views were separate. Convergence is occurring not just across the technology and future scenario curves, but also the various aspects of social change. So in the interest of maximizing future thinking impact, I have combined the two views and will describe a connecting the dots scenario. First, the new future scenario visual:
A must read on six mega-trends, their tipping points and societal impacts. I recommend this for anyone with interest in where the world is heading, and/or tasked with future thinking in the context of strategy. I commend the World Economic Forum for their efforts here, as education is likely to spur action. The six mega-trends are:
- People and the internet
- Computing, communications and storage everywhere
- The Internet of Things
- Artificial intelligence (AI) and big data
- The sharing economy and distributed trust
- The digitization of matter
Here is a tipping point timeline from the report:
Many leaders are struggling with the sheer number of future scenarios and some indication of when the tipping point may arrive. This material provides critical input into the scenario and response analysis process. Enjoy the read.
I expect the conversation regarding the Future of Business to intensify over the coming months. Evidence is mounting that business as usual is a thing of the past. In a recent post by SAP, they present ninety nine ways that digital will change business. As you look at the information presented, and see the number of shifts occurring at the same time, it’s hard to imagine a business landscape that weathers this storm unscathed. Here are examples of these shifts from the SAP post:
- At the current turnover rate, 75% of the companies in the S&P 500 in 2027, will be new (companies not currently in index today)
- By 2019, approximately one quarter of the entire U.S. workforce will be independent workers (self-employed, independent contractor, freelancer, temp contractor, etc.)
- By 2030, 10% of the largest companies in the U.S. will be virtual corporations (less than 10% of their workers will be in an office at any point in time)
- 50% of the U.S. Jobs lost in the 2008 recession were middle-skilled jobs, but only 2% of the jobs gained since then have been middle-skilled
- By 2025, there will be 10 global virtual currencies that will be considered mainstream. Their combined market value will exceed $5 Trillion, and Bitcoin will still be the largest.
- Private and commercial robot use will grow 2,000% from 2015 to 2030, creating a $190 billion market
- By 2030, 2 billion jobs will disappear – roughly 50% of all the jobs on the planet – as a result of technology advances
- 3D Printing usage will grow 2000% between 2015 and 2030
- Purpose-driven and value-oriented organizations outperform their competition 15 to 1
- By 2030, sensor use will grow 700,000%, solving nearly every human need such as cancer-killing chips
- By 2020, information will reinvent, digitize, or eliminate 80% of business processes and products
- Although 90% of companies view advanced and predictive analytics as important, less than 30% have currently deployed them, and only 30% have plans to do so
- There will be more words written on Twitter in the next two years than contained in all books ever printed
- By 2025, the total worth of IoT-enabled technology is expected to reach $6.2 trillion – most of that in healthcare (2.5 Trillion) and Manufacturing (2.3 Trillion)
- Within the next five years, more than 90% of all data from IoT will be hosted in the Cloud, reducing the complexity of supporting IoT “Data Blending
Just a small sample (more via the link above) supporting the notion that the future of business could look considerably different than its past. I’ll pursue the future business landscape in up-coming posts.
Part three of Anticipating 2025 will summarize the third section of the book. This section focused on redesigning artificial intelligence, with a look at six important questions and the exploration of human-machine mergers. The six questions explored in this section are:
- Can we create a human-level artificial intelligence?
- If so, when?
- Will human-level artificial intelligence lead to super-intelligence?
- If super-intelligence arrives, will we like it?
- Can we upload our minds to computers?
- Can we de-risk the arrival of super-intelligence?
Like the first two sections, this section forces us to look at disruption through a different lens. Granted, the path forward is highly speculative, and even the most optimistic scenarios are likely years away from having transformative implications. Nonetheless, it does force us to broaden our lens beyond traditional views. For example, I’ve focused on the automation of knowledge work and all its ramifications, while the authors (Calum Chace, Martin Dinov, and Elias Rut) focus on creating super-intelligence by uploading our minds to computers. They explore a human-machine merger that they see as the enabler of super-intelligence benefits realization. This merger in the author’s view is the only way to avoid creating our successor. So yeah, that’s a little more impactful than automating knowledge work.