Predicting the future is a business in itself, and experts, futurists, scientists, engineers, and others are constantly sharing their thoughts about the future. And this business has an incredible impact on society, whether or not the predictions come true.
For example, let's look at just one study about the future. McGraw-Hill's 1970 Survey of Technological Advances. As expected, the experts were hit and miss.
They got it right about technologies that were understandable and increasingly adopted at the time of the study, such as the expansion of plastics in a variety of applications, the proliferation of electronics in patient monitoring, electric vehicles, and the use of computers in business. The more complex the technology under consideration, the less accurate the predictions will be. For example, 3D TVs would not be widely available by 1980, cancer treatments would not be available by 1990, self-driving cars would not be available by 2000, and cashless society would not be available by 2010. was not realized either.
What's the deal? Predicting the future of technology often amounts to extrapolating past and current technology trends. However, forecasters cannot know everything and will miss out on innovative technologies and their impacts. For example, those surveyed expected the widespread use of computers in business and manufacturing, but Gordon Moore's prediction in 1965 and Moore's Law that billions of people around the world would I underestimated how to get it.
Predicting the future of technology is much more difficult today than it was half a century ago. With so much change and convergence happening so quickly, How can someone today asked to predict the future of technology predict when a game changer will emerge and disrupt industries and our way of life?
Consider the impact of ChatGPT's release and rapid scaling. ChatGPT has changed the worldview of almost everyone, except for a small number of workers who had previous experience with generative AI. As Bill Gates reminded us in the early days of personal computing, the software industry was small. Now that the company is a dynamic global giant and he is focusing on AI, innovation will come faster.[i] So it's reasonable to expect watershed technologies like ChatGPT to arrive sooner. So what can you do?
America must prepare for waves of change, disruption, and opportunity.
Of course, rapid technological change is not just happening in generative AI. The bioeconomy is growing rapidly as well, with thousands of laboratories using his CRISPR gene editing technology to expand the possibilities of biotechnology, and synthetic biology rapidly developing. Digital technologies continue to expand across numerous physical, virtual, social, and personal realms. Automation is accelerating and self-driving cars are on the streets. We are on the brink of several new eras. This is the era of clean nuclear energy. quantum era. And a new space age. And so on – everything converges, creating an unprecedented feedback loop between one and the other.
How can you gain a competitive advantage without knowing about the impending technological disruption?
First, we need to strengthen our predictive capabilities through greater collaboration and communication, and extensive use of technology and modern, agile business models. Second, we respond to waves of technological change by equipping ourselves with the best technology, talent, and infrastructure to ride the wave of technological change rather than being swallowed by it. We need to build a more adaptive and flexible innovation ecosystem. These recommendations — think of them as a sketch of your innovation blueprint. — would be a good start:
- Establish channels from the research community to rapidly transfer research and development (R&D) results and new technologies throughout the industry.
- Review national research and development and technology plans, programs, and policies more frequently. Establish on-ramps to quickly pivot to new opportunities and off-ramps when technological paths change. But we also need to persist in the basic research that allows us to push the frontiers of science and technology and create new futures.
- Regulatory mechanisms need to speed up. For example, multiple versions of ChatGPT and Runway generated video models were released by mid-2023.[ii] The Biden administration's executive order on artificial intelligence was issued in October 2023, but it will take time to budget for new initiatives. Congress has not passed any legislation to regulate AI. Countries are moving faster, but this is likely to create a patchwork of rules that will be cumbersome and costly for companies to comply with. Meanwhile, the EU is trying to set its own rules.
- Enabling more people to participate in ideation, product design, and development requires new kinds of infrastructure. In addition, they must address the increasing demand for computing power that AI consumes and the demand for data for training.
- Our technology hubs must be ready to quickly mobilize diverse assets such as talent, research and technology, capital, business capabilities, entrepreneurs, and start-ups to take advantage of new technologies faster. It won't.
- Universities and training providers need to produce skills at scale as new technologies expand and ease the transition for people displaced by disruption and change.
- It is important to remember that markets often reallocate resources to quickly exploit opportunities, more quickly and efficiently than government plans. We must lower the costs of market entry, new business formation, and disruption needed to take full advantage of technological disruption.
Now more than ever, our future competitiveness and prosperity will depend on the timely and efficient allocation and reallocation of productive resources to take advantage of a plethora of new technology opportunities. What we need to focus on is optimizing the speed and scale of our innovation ecosystem. The above recommendations do just that by reducing friction and fostering innovation. What ideas would you add to the mix?
[i] The age of AI has begun, GatesNotes, Bill Gates' blog, March 21, 2023.
[ii] Generative AI Predictions for 2024, CB Insights, 2024.
follow me twitter Or LinkedIn. check out my website.
