Many trends, in particular the convergence of multiple technologies which are improving exponentially, continue. Climate change will continue to be a most pressing issue, especially as we eat our way through our carbon budget.
As Bill Gates said, “Most people overestimate what they can do in one year and underestimate what they can do in 10 years.” Likewise, most annual predictions overestimate what can occur in a year, and underestimate the power of the trend over time.
Here are 18 areas which I think will be interesting to watch in the coming year:
1. International relations, the political economy, and governance will desperately need new design patterns as we enter a new phase of the digital revolution.
These should be developed in the public sphere with a wide range of participants. Three major themes to explore:
- The massive global platforms—Facebook, Google, Amazon, and the like—are defining a new political economy. Their corporate sovereignty will chafe with states’ own sovereignty. Those same nations will curry favor with the platforms to win the putative economic benefits provided by them. The large platforms know that governments will seek to rein in their power through regulation or legislation. These firms will accelerate their efforts to secure platform advantage and raise the baseline from which their settlement will be judged in the years to come.
- National AI strategies will emerge from more countries. The result? More grounds for cooperation and more reason to argue about intellectual property, privacy, data, and license to operate.
- Silicon Valley’s political culture—and how that has been codified into software, corporate culture, and strategy—will continue to smell. The Valley will hire outsiders to fix these problems or, more likely, just for the optics. This will take years. And before we’ve tackled that smell, crypto whizzes will establish governance mechanisms on emerging blockchain networks. They will do so with a narrow, ideological framing that will threaten to hurt us in the coming decades, by which time these networks will mediate many of the resources we need. This matters because information technology systems affect how we build our understanding of the world; they affect how we perceive our set of choices; they affect how we act in that world. In short: they affect our understanding both of the “is” and the “ought.”
2. While Silicon Valley leads, both innovation and scaling increasingly occur across the globe.
Europe and Central America lead the way in decarbonizing their energy chains. China is making huge strides in large-scale electrification of its urban transport systems. Its focus on AI, supported by the state and its homegrown tech giants, will show up as novel methods and large-scale implementations. And not just in personal surveillance.
The U.S., with its declining health and social outcomes and turn inward, will become less appealing to some entrepreneurs. And its business culture, focusing solely on corporate profits, will lack the motives to innovate in areas that affect the social fabric (for the collective good). Curiously, the European Union will provide room for innovation because of its ability to bring broader groups of stakeholders together than competition alone can foster. In particular, watch the innovation around open banking and privacy in Europe this year.
Leapfrogging in other innovation hubs will continue as well. We may not see an African firm to rival America’s tech giants anytime soon, but we will see meaningful innovation in fields like ag-tech and distributed power generation.
However, the largest firms in the world will hail predominantly from Silicon Valley, and one, most likely Apple, will exceed $1 trillion in market cap this year.
3. More money will flow into technology but it will be concentrated at later stages.
Following Softbank’s lead, funds bigger than $5 billion will abound now that the investment case of platform monopolies is well understood. These will seek to back emerging winners at a regional and global level (look at Careem and Didi Chuxing in ride sharing, for example). This may create funding gaps at earlier stages in the market, as already evidenced by the seed capital slowdown in Europe and the U.S.
4. The AI software stack will continue to diverge from traditional software.
This will include:
- Novel interface mechanisms. One will be voice, both as an input and as the output. The second will be images, where embedded cameras will provide large-scale inputs to machine-learning systems. (One example will be the growth of affective computing applications.)
- Specialist hardware (think Google’s TPUs and others) and novel frameworks (TensorFlow and its competitors).
- Cloud-to-edge computing, as we deliver an increasingly large proportion of intelligence at the locality where it is needed.
- A new paradigm of software development (where the best developers nurture highly parameterized models and cajole the training data to feed them).
5. Artificial intelligence will be the technology investment priority for large firms.
After years of prototypes, automation technologies and AI software now dominate the CIO’s agenda. They will invest and invest big. One group of winners will be the crop of 2013/2014 vintage AI startups now maturing into serious businesses with meaningful revenues and growing fast. The best firms, incumbent and startup, will combine AI investment with strategic and organizational change. Those same firms will move from simple notions of data supply chains to rethink their business model around data network effects and AI lock-in loops.
Firms that view AI not as a tool with which to expand their offerings but merely to cut costs will become lords of an ever-diminishing manor.
6. We will increasingly demonstrate how AI is augmenting human capabilities.
We will see more evidence for the tangible benefits AI tools can give us individually, and we’ll increasingly witness the power of the AI-augmented human.
The collective efforts of the research community continue to impress us, especially as we see low-hanging breakthroughs in areas outside of vanilla deep learning, such as reinforcement learning, adversarial networks, one-shot learning, and unsupervised methods.
(By the way, we’ll be barely any closer to human-like intelligence and no closer to artificial consciousness.)
7. The discussion on how AI will impact employment will shift from solely focusing on the elimination of jobs to how best to help workers accommodate the inevitable change.
Different countries will take different approaches. Those which combine an investment in social goods (like education and a safety net) and maintain a healthy approach to entrepreneurship and innovation will do best.
We will also make more progress in understanding questions of trust, fairness, and justice in algorithmic systems. Sensible boards, prompted by legislators, regulators, and activists will make ethical AI a top-table issue.
8. Cryptotechnologies will become more important and start to demonstrate their utility.
We’ll see AI developers increasingly experiment with the fruitful combination of AI and blockchain. These areas include how to build a data commons to incentivize the sharing of data, allow the sharing of models, and using blockchains and smart contracts for individual AIs to mediate their machine-to-machine interactions.
9. Sordid revelations in crypto-speculation will be outweighed by the wall of money entering the assets class.
Asinine press releases, speculative investors, and shady enablers get out into the market much faster than the technology can become useful. This lurid funk will obscure technology progress as more out-and-out frauds are met with regulatory intervention and commentators watch speculators from the safety of their schadenfreude pulpits.
Continue reading the full article at https://www.technologyreview.com/s/609868/18-exponential-changes-we-can-expect-in-the-year-ahead/
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