Autonomous vehicles (AVs) are at the forefront of technological advancements and emblematic of  inextricably linked upside potential and downside risks in artificial intelligence technologies. Vance Wagner, the panel’s moderator and Energy Foundation’s director of strategic partnerships in China, linked this to a universal visceral reaction to AI application and a widespread recognition that self-driving cars are revolutionary. As automobile and tech companies continue to apply artificial intelligence into manufacturing driverless cars, many question what this technology means for the future of mobility. The summit’s opening panel, “Future Mobility” discussed the role of AI in transportation and what a fully autonomous mobility infrastructure will look like in China and the United States moving forward. Recognizing that AV technology and implications bleed into all industries, the speakers applied their different backgrounds in areas of investment, industry, technology and regulation to examine measures that policymakers and executives must pursue to safely adopt fully autonomous vehicles into society in a positive manner. U.S.-China AI collaboration prevailed the discussion in alignment with the summit’s overarching theme. KEY TAKEAWAYS The future of AI-powered mobility requires a paradigm shift. While an AI-powered mobility infrastructure will improve transportation, self-driving cars have accompanying regulatory, societal, cultural and technological implications. The question is not whether the technology behind driverless cars exists or if the finished product can be achieved. Instead, it is how the technology should be implemented into society to guarantee standards for safety and ethics are maintained while gaining  efficiency. To move forward in achieving a future of fully autonomous mobility, regulators, investors and engineers must recognize AVs’ disruptions and find ways to alleviate them.
  • AV infrastructure requires a sharing environment. While the status quo of transportation is privatized car ownership, autonomous vehicles transition away from privatization towards ride sharing and public ownership. The practice is important to implementing AVs into everyday life and achieving technological accessibility. Following a UC Davis “Three Revolutions in Urban Transportation” report, widespread ride sharing is essential to future mobility, as are electric and autonomous vehicles. By conserving energy, cutting emissions, decongesting highways, lowering transportation costs, freeing up parking spaces and improving urban livability, ride sharing will revolutionize urban transportation.
  • Vehicles are more than transportation tools. Cars are traditionally a means of getting from point A to B. Moving forward in mobility’s future however, autonomous vehicles will adopt more entertainment or pet-like features, following Tao Wang, Investment Director at SAIC Capital. This is similar to how AI technology has diversified and expanded communicative practices with the advent of smartphones: telephones are no longer simply communication tools. With AI-powered mobility, humans will maximize their commute with new activities as time is no longer consumed by the driving practice. Thus, AVs’ implementation should be associated with increases in human productivity.
  • AI-focused transportation needs to have goals and meet them. Zoox, a U.S.-based self-driving car company, sets goals related to human safety and environmental protection as the company builds fully autonomous vehicles from the ground up. Bert Kaufman, Head of Corporate and Regulatory Affairs at Zoox, prioritized AV goals when discussing what an AI-powered mobility future should look like. In addition to prioritizing AI technology in automobiles, The Nissan Research Center in Silicon Valley focuses on AVs’ impact on humans in regards to safety. As AVs inspire a societal paradigm shift, standards of zero fatalities and zero emissions should be underscored when testing and implementing technology.
US-China AI cooperation is necessary. Many perceive that China and the United States are in a constant rivalry, especially in terms of technological innovation. Cooperation in tech and business spheres dissolve that misconception as those in the tech and finance industries recognize that collaboration can cut costs, increase efficiency and achieve results faster.
  • Tech sharing and partnerships should occur across borders. As the race to AV realization is not a one player game and requires a wide eco-system, cross-border and cross-company tech cooperation will make an AI-powered mobility future come faster, creating a circular economy for mobility. Baidu’s Apollo project, an open source platform, unites OEMs, Tier 1’s and sensor manufacturers from both China and the United States in creating an environment of tech collaboration. Nan Zhou, Baidu Changcheng Fund’s Investment Director, equated this approach to Google’s Android Open Source Project (AOSP) since both create a standardized operating system that is available to manufacturers. Sharing road data and codes, Zhou maintained, will contribute to the AV effort by making data more abundant and accessible.
  • Business models can capitalize on both Chinese and American markets. The future of mobility and its accompanying paradigm shift will disrupt automated vehicle business models. GGV Capital venture partner, Jason Costa maintained that neither China or the United States have figured out proper AV business models for the future, but predicted that there will not be competition between the two nations in that regard. Companies should recognize that they can capitalize on both the United States and China’s large markets for AI-powered mobility.
  • Chinese tech and road deregulations provide first-mover EV advantages. Efforts pursued by the Chinese government in terms of environmental mandates and deregulations have fostered an AI-friendly environment within the country. As the Chinese government has eased road regulations, data can be quickly and efficiently gathered to the benefit of Chinese tech companies. The mandate to completely phase out the combustion engine in China by about 2040 (although no deadline was specified) has helped position China as the largest market for electric vehicles (EV). Zhou believed that China will be the first to adapt to driverless cars because of its first-mover advantages in electric vehicles and its regulatory environment, advising that the United States should adopt similar methods in its regulation in future mobility.
  • The US and China have varying nation-state regulation. Regulation is the biggest challenge to implementing a fully autonomous vehicle infrastructure. China has less AI regulations than the United States. The speakers viewed this as a Chinese asset, forecasting that though the United States leads in technological capabilities right now, China’s deregulatory environment will close the tech gap. America’s federalism structure and its accompanying municipal-state-federal legal framework complicates AV infrastructure and adoption. Wang said that comparing the United States to China in terms of governmental projects, programs and regulation is like comparing apples to oranges: though China tends to finish projects or implement programs more quickly due to less red tape, American infrastructure lasts longer. The future of mobility is as much or more a regulatory issue than a technological challenge.
Cultural and geographical driving differences complicate AV implementation. Differences in geographical driving practices makes universal AV implementation difficult. As self-driving cars capture road data to understand driving habits, cities’ unique road systems and individuals’ adaptive driving habits serve to localize AV technology.
  • Driving practices are provincial. Driving in Beijing is drastically different from driving in Palo Alto. Not only is the infrastructure unique in both locations and different in terms of urbanization, but Chinese and American drivers drive differently. Though many assert that if you can drive in China, you can drive in the United States, Tao Wang noticed that is not the case, providing his friend—who failed his U.S. driver’s test five times even though he is considered a good driver in China—as an example.
  • Different driving habits makes cross-border road data sharing difficult. Locational driving dissimilarities caused both Tao Wang and Dr. Maarten Sierhuis, Chief Technology Director of Nissan Research in Silicon Valley, to state that AV technology is also provincial. They recommended that China and the United States test and research AV technology in their respective locations with Dr. Sierhuis weary that road data and deep learning will not account for geographical driving differences, calling for AI techniques outside of deep learning. Kaufman maintained that competition and collaboration should occur between cities and states in this regard before setting out to optimize AV technology internationally. These sentiments contrast with Zhou who asserted that sharing road data between the U.S. and China is important to AV development and will help both countries get closer to AV implementation.
Humans are the centerpiece of AI. Many associate artificial intelligence with human substitutability. Instead, AI technology should focus on bettering humans and improving the state of humankind to make the world more livable. Though the extent of human involvement and which self-driving car level to pursue in the future of mobility is somewhat contested, there is wide consensus that humans are AI’s main focus of attention.
  • Artificial Intelligence is a tool to improve mankind. AI technology intends to make humans happier, healthier, better, more efficient and ultimately smarter. Technological advancements enable humans to learn and problem-solve faster and faster. Wang argued that time and technology will evolve the human brain and grow its creative capacities, using the rising generation’s superior intellect as an example. Not only will AI technology improve human intellect, but also the surrounding world by tackling future and current safety, environmental and urbanization challenges.
  • AI-powered mobility requires human involvement. Sierhuis voiced his concerns over complete autonomy, instead calling for a concerted relationship between humans and autonomous systems. Stating that fully autonomous cars are dangerous and human intelligence is still the status quo, he advised coupling AVs with human supervision, with humans in a control setting with the ability to step in during unpredictable driving conditions such as road construction. Rather than having level 5 AVs, he advised striving for level 4 vehicles with the intent to incrementally test from there.
  • AVs are safer than human drivers. Wang argued, however, that fully autonomous, level 5 vehicles are safer than transportation with human involvement. This is due to human driving unpredictability. As humans cause 94 percent of crashes leading to road fatalities, Kaufman noted that AI and its application to vehicles can improve that statistic and work towards safer transportation. 
AI needs to solve more problems than it creates. An AI-powered mobility future should benefit the world and its inhabitants—whether in terms of safety, productivity or environmentalism. Artificial intelligence is a tool for good as it fosters cross-border cooperation, evolves the human mind, creates safer roads and helps protect the environment. In the paradigm shift towards implementing fully autonomous vehicles, AI should have positive impacts.
  • The future of mobility should create win-win scenarios. Society will adopt the three revolutions to urban transportation (EVs, AVs and ride sharing) more effectively if multiple parties benefit from their implementation. Uber and Lyft serve as key examples. Both companies use market-driven and efficient solutions to overcome setbacks and obstructions to carpooling that traditionally prevent individuals from ride sharing. Specifically, by deciding to carpool, customers pay less, companies profit from driving more riders and cities are less congested by freeing up parking space and decreasing the number of drivers on the road.
  • There needs to be zero fatalities and zero emissions in transportation. The collective goal to achieve zero emissions and zero fatalities in the future frame AV actions and discussions. In order to achieve the goal, tech companies, regulators and investors must prioritize the safety, mobility and sustainability trifecta, which assesses the effectiveness of connected and automated vehicle systems and their application. China and its combustion engine mandate shows that the country is taking the time, gaining the support and investing in needed public and private research to meet safety and emission goals.
  • The timeline towards fully autonomous vehicles is uncertain. A fully autonomous vehicle infrastructure is a work in progress. Dr. Sierhuis forecasts that 95 percent of AV usage will be achieved in the next five to 10 years (depending on definitions of safety and autonomy) but the additional five percent will likely take two to four times that period due to hurdles in technological perceptions and safety implementations. Costa viewed implementation of level 5 autonomous vehicles to be at least three to four decades out. However, Zhou predicted autonomous driving will come in a few years. But there has been significant progress in pursuit of AV implementation, strengthened by cross-border cooperation.

The views presented in this article are the author’s own and do not necessarily represent the views of any other organization.