The traditional build-and-expand approach is not a viable solution to keep roadway traffic rolling safely, so technological solutions, such as Autonomous Vehicles (AVs), are favored. AVs have considerable potential to increase the carrying capacity of roads, ameliorate the chore of driving, improve safety, provide mobility for those who cannot drive, and help the environment. However, they also raise concerns over whether they are socially responsible, accounting for issues such as fairness, equity, and transparency. Regulatory bodies have focused on AV safety, cybersecurity, privacy, and legal liability issues, but have failed to adequately address social responsibility. Thus, existing AV developers do not have to embed social responsibility factors in their proprietary technology. Adverse bias may therefore occur in the development and deployment of AV technology. For instance, an artificial intelligence-based pedestrian detection application used in an AV may, in limited lighting conditions, be biased to detect pedestrians who belong to a particular racial demographic more efficiently compared to pedestrians from other racial demographics. Also, AV technologies tend to be costly, with a unique hardware and software setup which may be beyond the reach of lower-income people. In addition, data generated by AVs about their users may be misused by third parties such as corporations, criminals, or even foreign governments. AVs promise to dramatically impact labor markets, as many jobs that involve driving will be made redundant. We argue that the academic institutions, industry, and government agencies overseeing AV development and deployment must act proactively to ensure that AVs serve all and do not increase the digital divide in our society.

翻译：传统的“建设-扩展”方法并非保障道路交通安全的可行方案，因此自动驾驶汽车（AV）等技术解决方案备受青睐。自动驾驶汽车在提升道路承载能力、减轻驾驶负担、提高安全性、为无法驾驶的人群提供出行便利以及改善环境方面潜力巨大。然而，它们也引发了关于社会责任的担忧，涉及公平性、公正性和透明度等问题。监管机构主要关注自动驾驶汽车的安全性、网络安全、隐私和法律问责，但未能充分解决其社会责任问题。因此，现有自动驾驶汽车开发商无需在其专有技术中嵌入社会责任因素，这可能导致技术在开发与部署过程中出现逆向偏见。例如，自动驾驶汽车中基于人工智能的行人检测应用在光线有限的环境下，可能偏向于更高效地检测特定种族人群而非其他种族人群。此外，自动驾驶汽车技术成本高昂，其独特的软硬件配置可能超出低收入群体的承受能力。同时，自动驾驶汽车生成的用户数据可能被企业、犯罪分子甚至外国政府等第三方滥用。自动驾驶汽车还可能对劳动力市场产生重大影响，导致许多涉及驾驶的岗位被淘汰。我们认为，负责监管自动驾驶汽车开发与部署的学术机构、行业及政府机构必须主动采取行动，确保自动驾驶汽车服务所有人，而非加剧社会的数字鸿沟。