As autonomous vehicle (AV) technology evolves, regulators must address growing concerns about the realities of having these vehicles on roads around the world. Four new policy papers from the Berkman Klein Center for Internet and Society at Harvard University outline the main issues and provide policy suggestions. ITU News caught up with Aida Joaquin Acosta, the papers’ author and Fellow at the center, about the key takeaways.
Regulators need to understand the complexity of AV technology and its capabilities and limitations, to avoid underregulating or overregulating AVs. Underregulating could endanger civil rights, and overregulating could hamper innovation and delay spreading their benefits among society.
AVs are complex: they are more than a vehicle with a camera, and their impacts go beyond traditional safety and security concerns.
‘Governments should consider the potential benefits and challenges of AVs holistically and from different perspectives.’ – Aida Joaquin Acosta, Fellow, Berkman Klein Center at Harvard University
AV technology is comprised of numerous systems including sensors (e.g., cameras, radars, ultrasounds and LiDARs) that generate massive amounts of data; and an Artificial Intelligence (AI) system, which commonly use deep learning and neural networks techniques to analyze the data and make decisions while driving.
The complexity of AVs is further increased by their interactions with traditional vehicles and pedestrians, as well as their communications with other AVs, infrastructure and other devices.
AVs may challenge cybersecurity, privacy, ethical norms, environmental and landscaping schemes, mobility and accessibility paradigms, use of resources, or sectorial employment.
In the AV papers, I discuss three main challenges to regulating AVs:
To help with these issues, the paper suggests three practical tools relevant to each challenge:
Governments should consider the potential benefits and challenges of AVs holistically and from different perspectives, as the potential net impacts of AVs are not clear, and balanced public policies can help optimize net outcomes.
The SWOT analysis shows that potential benefits can easily transform into correlated challenges, and vice versa. For instance, AVs could reduce the environmental impact of road traffic by decreasing CO2 emissions via more efficient driving.
However, AVs could contribute to more CO2 emissions by adding more vehicles to the roads, for example, by allowing the use of vehicles by wider sectors of the population, or by increasing highway capacity via shortening the distance between vehicles. A comprehensive analysis of benefits and challenges will help to develop more effective policies.
Furthermore, the SWOT analysis reveals key assets that governments can use to increase the performance of public policies, as well as weaknesses that they should work to mitigate.
‘It is vital to maintain a fluent dialogue with industry and stakeholders during the whole regulatory cycle of emerging technologies such as AVs and, more generally, AI.’
For example, governments can promote technology that prioritizes social values or educate society on the use and risks of the technology; and governments can work to reduce their lack of specialized technical knowledge, improve interdepartmental coordination, or revise existing laws to reduce obstacles to innovations.
To be successful, each best practice may need to be adapted to the specific context of its region; however, there are some mechanisms that can work well in many cases.
For example, in my opinion, it is vital to maintain a fluent dialogue with industry and stakeholders during the whole regulatory cycle of emerging technologies such as AVs and, more generally, AI.
For regulators, it is hard to predict the impacts of these technologies before placing them in the market. And working closely with the agents that develop and interact directly with the technology — from examining policy options, to designing a clear regulatory framework, to implementing and reviewing regulations — can help to reduce some of these uncertain impacts and produce more effective regulations.
There are several examples of this best practice.
For instance, the European Commission (EC) created GEAR 2030, a High-Level Group which included governments, industry and stakeholders in order to make recommendations on European AV policy.
The German government created a multidisciplinary Ethics Commission on Automated Driving, bringing together academia and different stakeholders to develop ethical guidelines for AVs.
The government of Singapore has developed a clear regulatory framework and close collaborations with AV companies to develop AV testing specific to the project.
In order to prepare, regulators can:
Views expressed in this article do not necessarily reflect those of ITU.
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