Tom Weeks, Transformation Director & Chief Strategy Officer, Informed Solutions
The transport and mobility sector is undergoing profound transformation, spurred by changing needs and attitudes, net zero de-carbonisation policies, Mobility as a Service offerings, connected and automated 车辆, and tighter competition.
这种转变很大程度上是数据驱动的——十大网博靠谱平台用户的现有数据的范围和数量, 车辆, transport options and services offer huge potential to improve mobility, create new business models, and improve the user experience. Given this, 毫无疑问，该行业看到了数据科学进步所带来的潜力, AI and machine-learning, and continues to invest heavily in data-driven innovation.
Earlier this year, we attended the techUK Transport AI conference. That event reinforced how bold the sectors vision for AI is, the extent of investment in it, and the potential value that it can bring. Understandably, much of the focus was on exploring the use cases for AI, highlighting the benefits and risks, and on running pilot projects to prove safety and viability.
A common theme that stood out is that, whilst there are lots of promising pilot projects, 目前还没有一条明确和一致的道路，可以将人工智能的基层创新扩大到地区和国家层面，以充分发挥其潜力.
事实上，在该领域没有一个明确的扩展人工智能创新的路径，这并不奇怪. Regulatory and governance frameworks for AI are still being shaped and, until there is more certainty about what these will mean in practice, there will be caution about scaling beyond a certain level. 公众对人工智能的态度也参差不齐，并且可能会随着其他行业的发展而迅速而不可预测地发生变化. 了解人们对人工智能的态度，将是判断以创造信任和接受的方式扩大创新的最佳方式的关键.
Working through uncertainties like this isn’t easy, 但在全国范围内实施数据驱动的数字化转型的例子可以提供蓝图. 一个很好的例子是我们与英国交通部/英国环境与环境部联合空气质量部门的合作, 我们与谁合作推出了屡获殊荣的“空气清新区自驾”服务.
There were three key ingredients that made this work a success:
- We took a user-centred approach to delivery. 这包括与所有受影响行业的用户进行面对面的研究，以了解他们的需求和态度，并共同设计服务, building trust, confidence and buy-in in the process;
- 我们建立了由中央政府代表领导和治理的伙伴关系, local government and the private sector. This helped to drive collaboration, as well as bringing together the diverse experience and perspectives necessary to make the transformation work for everyone; and,
- 我们制定了一个“扩大规模的途径”，逐步从研究和开发原型中获得服务, to working proof-of-concept, to controlled pilot, to live national service. 安全, 在每个阶段都定义和评估了安全和准备标准，以控制通过通道的进展.
这些相同的原则和框架可以应用于扩展基于人工智能的创新，并证明扩展可以按速度完成, but in a safe and controlled way.
In summary, 我们认为，交通和移动部门现在应该开始工作，为将人工智能的基层创新扩展到地区和国家层面制定蓝图和途径. 该蓝图应以在该部门大规模实施其他数字化转型的范例和经验教训为基础，并由公共和私营部门合作制定. By doing this, 未来的交通运输最有可能实现人工智能的全部潜力, whilst ensuring that it is safe, 安全, and viable at the same time.
