Of course, classical human-imitative AI problems remain of great interest as well. However, the current focus on doing AI research via the gathering of data, the deployment of “deep learning” infrastructure, and the demonstration of systems that mimic certain narrowly-defined human skills — with little in the way of emerging explanatory principles — tends to deflect attention from major open problems in classical AI. These problems include the need to bring meaning and reasoning into systems that perform natural language processing, the need to infer and represent causality, the need to develop computationally-tractable representations of uncertainty and the need to develop systems that formulate and pursue long-term goals. These are classical goals in human-imitative AI, but in the current hubbub over the “AI revolution,” it is easy to forget that they are not yet solved.
Founders are comfortable in the chaos and disorder. In contrast, professional managers attempt to bring order to chaos and often kill the startup culture in the process. Venture firms realized that teaching a founding CEO how to grow a company is easier than teaching t…
he f…t the Nietzschean idea of the survival of the fittest. It must prize greater things in human beings. The ability to dream, defy, love, forgive, create, rebel. That is where real human breakthroughs come from, whether in art, literature, science, or politics. That is where peace and prosperity, lie. To genuinely value human potential, life, possibility, is the opposite of the survival of the fittest.
…crucial as public and private entities work together to understand what’s happening on our streets, because the data produced by digital coordination platforms are transforming how we govern our transport system. Traffic data doesn’t just help alleviate traffic jams, it is the foundation for future transport policies like road pricing. Travel demand data enables thoughtful integration of public and private transit services, and smarter allocation of subsidy dollars. As private-sector responsibility in transport expands, data is key to ensuring actions and incentives are aligned with the public interest — especially when questions of equity and affordability are concerned.
But information isn’t enough to ensure more coordinated use of transport infrastructure, particularly when the quickest choice for an individual (often driving) is at odds with what’s most efficient for everyone else. We need other mechanisms to resolve conflicts and contention for limited resources. That’s where incentives and enforcement come into play.
… These technologies expand the toolbox available to address longstanding transportation challenges. Better coordination could potentially help governments make the most out of existing roads instead of building new ones, expand access to jobs through more effective transit service, and reduce the need for vehicle ownership.
… and location technologies like GPS, are forming the basis of an entirely new type of coordination. Data is replacing concrete as we shift from the often-glacial process of coordinating people through the design and construction of new physical infrastructure, to people coordinating the use of existing physical infrastructure in real-time.