ΑΙhub.org
 

Ethics of connected and automated vehicles: a European Commission expert group report

by
02 October 2020



share this:
AIhub | EU flag

On 18 September the European Commission published a report on the Ethics of Connected and Automated Vehicles (CAVs). Written by an independent group of experts, the report includes twenty recommendations on road safety, privacy, fairness, AI explainability and responsibility, for the development and deployment of connected and automated vehicles.

The recommendations have been made actionable for three stakeholder groups:
1. Manufacturers and deployers (e.g. car manufacturers, suppliers, software developers and mobility service providers);
2. Policymakers (persons working at national, European and international agencies and institutions such as the European Commission and the EU National Ministries)
3. Researchers (e.g. persons working at universities, research institutes and R&D departments).

The aim of the report is to “promote a safe and responsible transition to connected and automated vehicles (CAVs) by supporting stakeholders in the systematic inclusion of ethical considerations in the development and regulation of CAVs”.

The report recognises the potential of CAV technology to deliver benefits, such as reduced fatalities and emissions, but also recognises that technological progress alone is not sufficient to realise this potential. In order to deliver the desired results, the future vision for CAVs should incorporate a broader set of ethical, legal and societal considerations into the development, deployment and use of CAVs.

The 20 ethical recommendations are as follows:

  1. Ensure that CAVs reduce physical harm to persons.
  2. Prevent unsafe use by inherently safe design.
  3. Define clear standards for responsible open road testing.
  4. Consider revision of traffic rules to promote safety of CAVs and investigate exceptions to non-compliance with existing rules by CAVs.
  5. Redress inequalities in vulnerability among road users.
  6. Manage dilemmas by principles of risk distribution and shared ethical principles.
  7. Safeguard informational privacy and informed consent.
  8. Enable user choice, seek informed consent options and develop related best practice industry standards.
  9. Develop measures to foster protection of individuals at group level.
  10. Develop transparency strategies to inform users and pedestrians about data collection and associated rights.
  11. Prevent discriminatory differential service provision.
  12. Audit CAV algorithms.
  13. Identify and protect CAV relevant high-value datasets as public and open infrastructural resources.
  14. Reduce opacity in algorithmic decisions.
  15. Promote data, algorithmic, AI literacy and public participation.
  16. Identify the obligations of different agents involved in CAVs.
  17. Promote a culture of responsibility with respect to the obligations associated with CAVs.
  18. Ensure accountability for the behaviour of CAVs (duty to explain).
  19. Promote a fair system for the attribution of moral and legal culpability for the behaviour of CAVs.
  20. Create fair and effective mechanisms for granting compensation to victims of crashes or other accidents involving CAVs.

All of these points are considered in detail in the report and are accompanied by suggested actions for each of the stakeholder groups.

Read the report in full to find out more

Ethics of connected and automated vehicles – report
Ethics of connected and automated vehicles – factsheet
Ethics of connected and automated vehicles – infographic




Lucy Smith , Managing Editor for AIhub.
Lucy Smith , Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



The Machine Ethics Podcast: AI readiness with Tim El-Sheikh

In this episode, Ben chats with Tim El-Sheikh about ethical AI as the smarter AI, the importance of a business AI strategy, getting data ready, and more.
22 October 2021, by

Join our team of AIhub ambassadors!

We are looking for people to join us as AIhub ambassadors.
21 October 2021, by

Interview with Lily Xu – applying machine learning to the prevention of illegal wildlife poaching

Lily Xu tells us about her work applying machine learning and game theory to wildlife conservation.
20 October 2021, by

What bird is singing? Merlin Bird ID app offers instant answers

The Cornell Lab of Ornithology’s free Merlin Bird ID app can identify bird sounds.
19 October 2021, by

Distilling neural networks into wavelet models using interpretations

We propose a method which distills information from a trained DNN into a wavelet transform.
18 October 2021, by

Cynthia Rudin wins AAAI Squirrel AI Award

Duke professor becomes second recipient of AAAI Squirrel AI Award for pioneering socially responsible AI.
15 October 2021, by





©2021 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association