The rapid advancement and complexity of Artificial Intelligence (AI) based systems has introduced a range of challenges, including liability related issues. In this blog post, we will consider some real-world instances of liability issues, particularly focusing on AI and liability.
AI and Liability in Autonomous Vehicles
Autonomous vehicles, which heavily rely on AI systems for navigation and decision-making, have been involved in accidents, raising questions about liability. For instance, a class action was started in early 2017 against Tesla over an automated vehicle’s autopilot system, claiming that it contains inoperative safety features and fault enhancements.
Proposed Solution: One potential solution is to establish clear regulations that define the responsibilities of manufacturers, software developers, and users in the event of an accident. Manufacturers and software developers could be required to conduct rigorous safety testing, that is, more than what is currently considered acceptable, before their products are allowed on the roads. Users could be educated about the capabilities and limitations of autonomous vehicles to ensure they use the technology responsibly. Furthermore, users should be provided with clear instructions on how to take control of the vehicle in case of an emergency.
AI and Liability in Facial Recognition Technology
Facial recognition technology, which uses AI to identify individuals from images or videos, has been known to misidentify faces. For example, the algorithm running the London Metropolitan Police’s facial recognition technology was reported at one time to have an error rate as high as 81%.
Proposed Solution: Companies developing facial recognition technology could be required to demonstrate the accuracy of their systems before they are deployed. Regular audits could be conducted to ensure the systems continue to perform accurately. A framework could be established to compensate individuals who are misidentified by the systems, in line with those currently implemented by the DoT in case airline luggage gets misplaced or a customer is involuntarily booted from the aircraft due to overbooking. Additionally, the use of facial recognition technology could be limited to specific contexts where its benefits outweigh potential harm.
3. AI and Liability in Healthcare
AI is increasingly being used in healthcare to diagnose diseases and recommend treatments. However, if an AI system makes an incorrect diagnosis or recommendation, it could potentially harm patients.
Proposed Solution: Healthcare providers could be required to verify the diagnoses and treatment recommendations made by AI systems. Patients could be informed that an AI system is being used and given the option to have a human healthcare provider involved in their care. Regulations could be established to hold healthcare providers and AI developers accountable in the event of errors. Moreover, patients should provide informed consent before AI is used in their care.
4. AI and Liability in Data Security
AI is often used in data security systems to detect threats and protect data. However, if an AI system fails to detect a threat, it could result in a data breach.
Proposed Solution: Companies could be required to have backup security measures in place in case the AI system fails. Regular audits could be conducted to ensure the AI system is performing effectively. Companies could be held liable for data breaches resulting from the failure of their AI systems. To mitigate financial risks, companies could consider liability insurance that covers damages resulting from AI failures.
Conclusion
Potential solutions like transparency in autonomous vehicles, improved accuracy in facial recognition technology, verification and patient consent in AI in healthcare, and backup security measures in AI in data security can help us address AI and liability issues and harness AI’s full potential.