The Liability of Artificial Intelligence's Moral Dilemma

What is Artificial Intelligence?

In the wake of the fourth industrial revolution, Artificial Intelligence (AI) has paved its way towards helping mankind. AI is defined as the ability of computer systems to perform tasks linked to human intelligence such as speech recognition.¹ AI is also capable of making decisions and is used to assist decision-making, as it is inevitably taking over the current market.² According to McCarthy, AI is defined as “the science and engineering of making intelligent machines, especially intelligent computer programs³”. Since these technologies are more reliable and intelligent compared to humans, it is important to determine whether AI may be liable for ‘moral decisions’ that cause damage or injury to the victim under the principle of negligence.

The moral dilemma in Artificial Intelligence (AI)

AI technologies are forced to make decisions and judgments. AI employs machine learning whereby it empowers machines to learn through experience and solving problems by employing predefined algorithms.⁴ These decisions and judgments are based on a set of algorithms that are incorporated into the system or programme. There is little human supervision, and AI is free to make its own decisions.⁴ By making decisions, AI is exposed to data. It requires an adequate amount of correct and non-biased data, which is a challenge in the real world.⁵ There is risk that an AI system would modify the real-world data according to its machine learning understanding, which might be biased or contain false information.⁵ Hence, increasing concerns are raised about the moral decisions made by AI. The following are several examples of the moral dilemma faced by AI technologies:

The question of morality in AI

In designing AI, the trolley problem is always posed in situations where AI is required to make important decisions.¹¹ This can be illustrated by imaging a situation where a trolley is charging towards five workmen on the track. The trolley is not able to stop due to defective brakes. A person is standing next to a switch where he can divert the trolley to another path. However, a single workman is present on another path. Thus, if that person pulls the switch to another path, the single workmen will die. On the other hand, if that person does not pull the switch and revert the path, five workmen will die.¹¹ Similar to AI, the person who holds the switch is the programmer. The difference is that the programmer is not a bystander. Therefore, his actions will bring about consequences, since he has to make decisions. However, the trolley problem does not solve the question of liability, as the trolley problem only considers how a vehicle should react or make moral decisions.

Liability arising out of the moral dilemma of AI by applying principle of negligence

Liability is often questionable when it comes to AI. Based on the scenarios discussed above, if the victims suffer any damage, they may seek recourse under the existing liability regime through the tort system, to claim compensation¹² under the principle of negligence. The negligence principle is recognised in the United States as well as in common law countries. In tort, the injured party will seek redress from the negligent conduct of the defendant.¹² The damages will be paid by the person causing the damages.¹² Thus, AI companies are always on the lookout, because these companies are the ones who have the best financial capabilities to pay damages.

This research seeks to discuss whether the principle of negligence may be used to claim damages that arise out of the ‘moral decisions’ of AI. It is pertinent to discuss the principle of negligence first, before analysing its basis for liability. Negligence in tort is defined in the case of Blyth v Birmingham Waterworks Co as “the omission to do something a reasonable man would do, or doing something which a reasonable man would abstain.¹³” To be held liable under negligence, several elements need to be satisfied: the duty of care, breach of duty, causation, and damage. Hence, to assess whether AI may be held liable under negligence, these elements are discussed in detail.

Duty of care

Under the element of duty of care, the classic case used under common law is the case of Donoghue v Stevenson, wherein reasonable care must be taken to avoid acts or omission that are likely to injure the person closely and directly affected by the defendant’s act.¹⁴ The duty of care was later extended in the case of Caparo Industries v Dickman and Others, where the court held that the harm must be foreseeable, there must be proximity between the plaintiff and defendant, and it must be fair and just to impose a duty of care.¹⁵ In determining the duty of care concerning AI, it might be less compared to the duty of care that does not involve AI.¹⁶

Other than that, since there are multiple parties involved in producing AI, a suitable question to ask is: who owes a duty of care towards whom?¹⁷ The number of parties involved may range from programmers, to engineers and manufacturers. Another question that arises is whether the traditional reasonable man’s test as applied in common law to determine negligence applies to AI. Similarly, in the United States, the standard of care is assessed using the reasonably prudent person.⁴ Since there is an absence of a particular standard for liability under negligence, an alternative of the standard of care, aside from the reasonable man’s test, may be applicable.⁴ A professional standard of care may be appropriate to be imposed, as the persons who created the software are regarded as professionals.¹⁸

Breach of duty

Breach of duty may arise in several situations, as follows:

Hence, establishing a breach is not easy, as there are many parties involved, especially when AI involves advanced technology.¹⁷ To prove liability involving multiple parties is not easy either, especially when AI adopts machine learning.

Causation

Causation and foreseeability is the main ingredient to establish liability under the tort of negligence.⁴ These issues must be confronted before establishing damage due to decisions made by AI, under the tort of negligence. To succeed in a negligence claim, it is material for the plaintiff to prove that there is a reasonable connection between the act of the defendant, and the damage caused.¹⁸ Thus, the challenge in proving the cause of the damage, or causation, is the multiple parties and the complexity involved in the programme, making it difficult to pinpoint the originating cause of damage.¹⁸

Furthermore, in establishing causation, the damage must be foreseeable.¹⁹ If the damage is unforeseeable, negligence cannot be established.^4,19 Thus, if AI reacts by making ‘moral decisions’, the damage in consequences of the act must be foreseeable.¹² If there is a lack of foreseeability in AI making decisions, there is a possibility that liability under negligence would not be blamed on anyone at all.⁴ According to Yavar Bathaee, the law “is built on legal doctrines that are focused on human conduct, which when applied to AI, may not function”.²⁰ This is because it is impossible to determine how AI would come up with the decision through internalized learning of a black box nature, hence making its decision unforeseeable.²⁰ It can be illustrated by the ‘moral decisions’ discussed, where an autonomous vehicle would fully recharge itself the whole night because the vehicle discovered by machine learning that it would perform better with a full battery.²¹ However, for the autonomous vehicle to fully charge itself, it releases carbon monoxide and thus endangered the household.²¹ The manufacturers may claim that it is foreseeable that autonomous vehicles would get into an accident. However, they never foresee that autonomous vehicles may kill anyone by the release of carbon monoxide.²¹ Thus, to develop a balanced law, the producers of AI must take precautions to evaluate the foreseeable risks of AI technology.

In assessing the elements of negligence, it is difficult to establish liability under the tort of negligence, due to the issues discussed above. Thus, it is a challenge to create AI that employs machine learning to be liable under the tort of negligence, since it seeks the negligence of humans, not machines.¹⁶

Possible liability for AI aside from principle of negligence

Product liability

Aside from negligence, product liability may also be considered to impose liability under the existing liability regime, as it may occur when there is a defect in the product manufactured.⁴ In the United States, product liability claims may also be brought under negligence, strict liability or breach of warranty.¹⁷ Since humans are not involved when AI robots make decisions based on machine learning, liability may move to product liability. Under this principle, it must be construed whether the algorithm used in machine learning is considered an actual product.⁴ There is no clear discussion on the status of the algorithm as a product. In determining the liability of AI by using the product liability principle under Malaysian law, the first crucial issue to be determined is whether the algorithm used in AI machine learning is recognized as a product or a service. If such an algorithm is determined as a product in AI, then the product liability principle can be applied to prove the liability of AI.

Strict liability

Another option to assign liability to AI is to adopt strict liability. Under strict liability, the manufacturer would be held liable, regardless of whether or not he is at fault.⁴ There is a possibility that manufacturers may be held liable for the decisions made by AI robots. However, it must be noted that if there are changes to the product after delivery, manufacturers may not be held liable under strict liability, unless the changes made to the product are foreseeable.⁴ Hence, concerning AI products that employ machine learning, the element of foreseeability must be construed to make manufacturers strictly liable. The absence of foreseeability when AI causes harm when using machine learning may lead to manufacturers not being liable.

AI personhood and claims pool

Instead of assigning liability to manufacturers or other parties, the conferment of AI personhood would make AI independently liable, where it is capable of being sued in court.²² Another option is to make it obligatory for AI to be insured or have a universal insurance claims pool to pay out damages.⁵ A no-fault liability scheme may be established by contributing to a claims pool to pay for damages resulting in harm by AI robots, where the claims pool may be contributed by the AI and robotics industry.⁴