Intelligent no-fault insurance for robots

“In the following decades, AI will continue to transform more fields and deliver astonishing advancements in convenience, comfort, safety and security. At the same time, however, AI will bring about new challenges. AI will offend, disrupt, crash, breach, incite, injure, and even kill in unexpected ways. Unlike traditional injuries, tort law11 will have difficulty finding the injuries caused by highly sophisticated AI to be the fault of someone’s negligence or some product’s defect.” (Yoshikawa, 2019)

“A complicating factor, however, is that machine learning decisions are hard for humans to understand. This is because the way the technology makes its decisions is not solely designed by a human developer – rather the technology learns patterns and relationships from data, and thereby builds a model of the process involved. Machine learning encompasses a range of techniques, and the level of comprehensibility varies across that range. At one end lie technologies such as decision trees, which embody chains of logic which lead to each possible decision, and thus allow the reasons for any particular decision to be explained. At the other end, neural networks identify patterns in large data sets and then make decisions based on pattern matching. Here it may not be possible for even the technology producer to explain a decision in terms of the logic and causation which the law looks for.” (Reed et al., 2016)

“It is only possible to draw two firm conclusions from the discussion above. The first is that it is far too early to devise a liability regime for machine learning generally, because in the current state of development of the technology the law would rapidly fail to accord with technological change. The second is that, both in respect of liability and the fundamental rights which underpin individual autonomy, society will need to make some difficult choices, because if machine learning is to be adopted widely then the existing legal and regulatory settlement will not cope adequately.”

[NOTE: Additional and very different levels of complexity are created for the legal liability and insurance of medical robots such as the da Vinci surgical robot, and for robotic prosthetic devices such as robotic exoskeletons. In order to avoid any discussion on those additional levels of complexity I do not consider medical products in this paper.]

“One evening a young lady named Laura is at a dance, partnering a ballroom dancing robot. The band strikes up with the music for a cha cha cha but performs it so badly that the robot mistakes the music for a tango. So Laura and her robot partner are holding each other but dancing at cross purposes, and very soon they fall over. The robot lands on top of Laura and, being quite heavy, breaks both of her legs. Laura’s father is furious, and calls his lawyers, telling them to commence legal proceedings immediately and “throw the book at them”.

But at whom should his lawyers throw the book? Should it be the dance hall, or the online store that sold the robot to the dance hall, or the manufacturer of the robot, or the robot’s designers, or should it be the independent software house that programmed the robot’s tune recognition software, or the band leader, or even the whole band of musicians for playing the cha cha cha so badly?

Some months later the trial opens with all of these as defendants. Expert witnesses are called – experts on everything from robot software to motion sensor engineers to the principals of dance music academies. What do you think would be the result of the trial? I’ll tell you – the lawyers do very nicely thank you.”

“Liability law is designed to achieve an efficient balance between the concern for physical safety and the desire for innovation. As a result, the basic tests for design defects and for instruction and warning defects have two distributional effects: (1) Sellers are liable for injuries caused by a failure to use a safer approach that costs less than the injuries it prevented; and (2) victims are not compensated for injuries where a safer approach costs more than the accidents that would have been prevented by the approach.” (Hubbard, 2014)

“requires answers to a wide range of questions that have not been sufficiently addressed by supporters of no-fault schemes. Because the proposed no-fault schemes will be funded as part of the cost of the activity of manufacturing or distributing automobiles, the proposals must not only identify the activity but must also identify the costs associated with that activity. For example, workers’ compensation insurance covers the activity of employment and the injuries incurred while working. Other focused schemes operate in a similar fashion. Would all injuries caused by the activity of manufacturing or of distributing automobiles be covered by the scheme, including not only those involving some possible “defect” but also those involving such things as: (1) human error in driving or in maintenance; (2) bad weather; and (3) situations where the autonomous system was somehow involved but not defective? The scheme would also have to address issues like the following: (1) the nature and level of benefits; (2) the types of injuries covered (for example, would noneconomic damages like pain and suffering be included?); (3) the persons covered (would relationship interests like loss of consortium55 be covered?); (4) coordination with other benefit schemes like workers’ compensation and social security; and (5) administration. Because the [accident fund] proposals fail to address these issues, they are so incomplete that they cannot be evaluated and thus should not be implemented.” (Hubbard, 2014)

“This proposal is based on the concern that, where an automobile is fully autonomous (driverless), “assignment of liability is more complicated” and “current products liability law will not be able to adequately assess…fault…[because] current law is too cost prohibitive insofar as expert witnesses are likely to be required by the plaintiff.”

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“In addition, a “strict liability” proposal will need to provide a new test for defective design, warnings, and instructions to replace the current cost-benefit approach.”88

“To the extent that artificial agents become increasingly complex, those who build or deploy advanced AIs and robotics will not necessarily have intent or foresight of the actions those systems may take. This is especially true for systems that can substantially change their operations through advanced learning techniques, or those future systems that might even become genuinely autonomous in generating their own goals and purposes, or even intentions.” (Asaro, 2016)

“At some point in the evolution of autonomous artificial agents, they might become legal and moral agents, and society will be faced with the question of whether to grant them some or all of the legal rights bestowed on persons or corporations. At that point, some or all of current liability law might apply to those AIs and robots that qualify as legal persons, though it might not be clear what the exact boundaries of a particular entity might be, or how to punish it.” (Asaro, 2011)

“Since vehicle functions are controlled by ADAS rather than by the driver, liability should be transferred increasingly to the technical system – and by extension to the manufacturer. Some experts in fact predict a general shift from driver liability to product liability in autonomous vehicles.”

“Given the complex nature of autonomous technologies, not only in their design but in how the technologies interact with each other and with humans, the task of assigning liability may be impossible to accomplish in a cost effective way with our current tort system. In addition, potential liability issues and uncertainty over just who may be liable could slow the development and adoption of autonomous driving technologies that offer so many benefits to society.”

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“So, who is liable in the event of an automobile accident? Some legal scholars suggest assessing responsibility using products liability principles and focusing on the driver’s level of reliance on the autonomous vehicle. In purely autonomous mode, probably the manufacturer is liable based on manufacturing defect or design defect. If autonomous mode is disabled, probably the driver is liable due to negligence. When switching in and out of autonomous mode, probably the driver is liable, except manufacturer’s liability may be extended even in cases of driver error due to manufacturer’s failure to warn, or warning defect. Determining the driver’s level of reliance on autonomous features can be problematic, especially if one debates the appropriateness of driver decisions to engage and disengage autonomous features. Another complication stems from the failure to warn or warning defect, whereby manufacturers have a duty to provide instructions on the safe use of their product and to warn consumers of hidden dangers. Situations that seem to be driver negligence could be turned into manufacturer’s liability if it can be shown that manufacturer training programs were inadequate for the general driving population.” (Eastman, 2016)

“an excellent argument that the shortcomings of no-fault insurance have more to do with how no-fault statutes are structured by state legislators and less to do with the concept itself. Their review of forty years of state experimentation with no-fault insurance shows that “data support the notion that no-fault is a far better compensation system than tort: it succeeds in paying more people faster and more in line with their economic needs.” (Eastman, 2016)

“Different approaches to the liability issue have been proposed, but revised no-fault automobile insurance maintained in the private sector offers the most benefits and the best chance of becoming a reality. America is a litigious society and one in which the party at fault is required to pay. As the determination of who is at fault becomes more difficult and costly, Americans need to accept a no-fault solution.”

“Drones are essentially robotic aircraft. They can be operated with a “pilot” sitting in a ground station, but many will have autonomous capabilities where the aircraft will operate on its own. These autonomous aircraft will operate through advanced software systems coupled with sensing hardware and GPS navigation packaged in a highly maneuverable airframe. A key feature will be an autonomous anti-collision system that must not only protect the drone from collisions with other drones but also protects it from collisions with birds, other aircraft, buildings and structures. The risks of crashes and incidents caused by drones in the national airspace are currently unknown. Risk profiles have yet to be determined due to the lack of available information. Insurance carriers may be able to extrapolate loss experience from the aviation industry but [this] will need to be adjusted for the issues of robotic autonomy in flight, autonomy in collision avoidance, and autonomy in critical issues such as lost links in which communications are cut off and the drone must make decisions on its own.” (Beyer et al., 2014)

“Anyone flying a drone is responsible for flying within FAA guidelines and regulations. That means it is up to you as a drone pilot to know the Rules of the Sky, and where it is and is not safe to fly.” (FAA, 2019)

“Software failure to perform as intended could cause a drone to crash resulting in personal injury or physical damage. Software can also fail by becoming corrupt, losing connectivity, or “crashing”, sometimes wiping or rendering itself unusable. The software could mistakenly send legally protected data to an unintended recipient resulting in breach notification liability. Software data in transit could be hacked by a criminal who steals the data, or the drone itself could be hacked and taken over remotely. Hackers could also gain access to video, camera, or other sensor feeds and use the information gained to commit other crimes. Owners and operators of drones will need coverage for these risks as well.” (Beyer et al., 2014)

“While FAA integration is a sufficient event … insurability is a necessary event before businesses can successfully use UAS [unmanned aerial systems] in the National Airspace System … because no business is going to want to be on the line for the liability concerns…Insurability will determine which sectors of the [drone] market will grow and which will die”. (Jenkins, 2013)

“Insurance companies face too complex a challenge in precisely assessing the risks associated with the production, use and diffusion of robots of various kinds. In particular, the complexity and novelty of robots causes the identification of the damages they may bring about in a real life environment to be extremely complex, diversified and hard to foretell, and hence manage. The same kind of technical malfunctionings may indeed determine very different outcomes once the device is used in different and ex ante1111 unrestrained environments. The complexity and to some extent opacity – if not inadequateness – of the legal framework further adds upon such considerations, causing the assessment of the risk pertaining to each party involved (be it the producer or user) to be even more complex. Indeed, in some cases, it is not even clear which party may be held liable, hence ultimately who should have an interest to acquire insurance coverage.

Overall, this may result either in the (i) refusal to insure some kinds of robotic devices, or (ii) the use of existing [insurance] contracts, which however may prove inadequate, or (iii) the charging of excessively high premiums, ultimately delaying the diffusion of robots as well as impairing the proliferation of a supply side of the economy (industry for the production of robots).” (Bertolini, 2016)

“The vast majority of accidents are caused by human error, and in theory by replacing human input with well programmed computers, the risks of driving could be substantially reduced. With less reliance on a human driver’s input, however, increased risk would be associated with the car technology itself. Computers can do many things that a human driver cannot: they can see in fog and the dark, and are not susceptible to fatigue or distraction. However, they can also fail, and systems are only as good as their designers and programmers. With an increased complexity of hardware and software used in cars, there will also be more that can go wrong.” (Yeomans, 2014)

“To address cyber risks, high standards of system resilience, such as robust data encryption, will need to be engineered. Consideration will probably also have to be given to how networking with other cars, infrastructure, and personal computers such as smartphones could impact the cyber security of a car.”

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“Cars are likely to deal in large amounts of data, and may be increasingly connected with existing technology such as smartphones and tablets. Through connectivity with other personal digital technology, as well as other cars and infrastructure, there could be potential for unwanted third parties to access data. Although cars already have computerised units, at present they tend to be isolated, not networked, and therefore at less risk. As cars become more connected, it could be possible for hackers to access personal data, such as typical journeys, or where a person is at a particular time, which could for example allow a burglar to know when a householder is not at home. It is also feasible that driving could be maliciously interfered with, causing a physical danger to passengers. There is potential for cyber terrorism too – for example, a largescale immobilisation of cars on public roads could throw a country into chaos.” (Yeomans, 2014)

“There is a risk that if this link was lost or disrupted, the aircraft would be out of control. To mitigate this risk, attention needs to be paid to the security and strength of data connections, and backup options should be considered in case the connection fails. One precaution that exists is for the aircraft to return to its take-off point if it loses signal, using systems such as Global Positioning Systems (GPS). Adequate sense and avoid capabilities would also mitigate the risk of an aircraft losing contact with its operator, as it should behave autonomously in choosing where it travels in order to avoid a collision.” (Yeomans, 2014)

“The new social and technological reality of connected and autonomous vehicles calls for the development of an EU-wide insurance remedy. Given the rapid developments in the market for autonomous vehicles, a special no-fault insurance, complementary to the injured party’s entitlement to social security benefits, replacing civil liability claims for damages, may provide for a flexible and satisfactory solution. Both in terms of legal certainty, its potentially wide scope of protection and efficient claim handling, it appears to outweigh the adversarial options under the PLD1313 and the national traffic liability laws.” (Evas, 2018)

“The development and use of intelligent machines faces tremendous challenges in current legal systems. Technological development is stifled by liability risks. Currently, the manufacturer or operator is held liable depending on the circumstances. Due to both the technological limitations for perfectly functioning machines and the unpredictable cognitive element, intelligent machines are not perfect and it is almost guaranteed that there will be failures causing harm. However, this is not an excuse not to aim for failure-free operation. Instead, the inevitable failures should be managed so that present economical or legal issues do not hinder the potential human development and prosperity enabled through the adoption of new technologies.”

“We propose a new kind of legal approach, i.e. the ultimate insurance framework, to solve the related legal and economical difficulties in order to support the technological pursuits. In the insurance framework, a machine can become an ultimate machine by emancipating itself from its manufacturer/owner/operator. This can be achieved by creating a legal framework around this ultimate machine that in itself has economical value. The first step in creation of a legal framework around the machine is to make applying for the insurance mandatory.” (Huttunen et al., 2010)

“…an electronically-driven monitoring process for law enforcement agencies, whereby they can check if a robot is adequately insured. If the detection method discovers that adequate insurance is not in place the robot will be temporarily disabled by an electronic message transmitted remotely and automatically, by the authorities, to its black box, so that the robot will not function, beyond announcing to its user that its insurance cover is inadequate or has expired. The monitoring system should not only disable uninsured robots, it should also report to the authorities any attempt to bypass the monitoring technology.

My proposal is that, when a robot is sold by its manufacturer, an appropriate insurance premium should be levied for its first year of operation. That premium is included in the robot’s selling price and until it is paid the robot will not function. One month or so before the paid insurance premium expires the robot’s owner would receive a warning message, from the insurer, that its insurance needed to be renewed. When the renewal payment is received by the insurer an electronic message is sent to the robot’s black box, instructing it to permit the continuing operation of the robot. But if the owner fails to renew the insurance by the due date the robot will cease to function, instead announcing “Please renew my insurance before you try to use me again.”

“The level of insurance should depend on the nature of the robot being insured. Many robots – for instance, small robots used primarily for entertainment – would only need to be insured minimally, if at all. Larger robots with more autonomous functioning – for instance, security robots that patrol a parking lot – would require greater coverage.”

“One of the beneficial effects of employing a wealth of historical robot accident data as a guide to setting insurance premiums, is that robot developers and manufacturers will feel the effects on their corporate bottom lines if their products are more accident prone than the average. The robot insurance system I envisage will be self-regulating for the robot industry, as makes and models that are accident-prone will rapidly attract higher insurance premiums, thereby pushing up their retail costs and encouraging consumers to purchase products with better safety records. Similarly, robot owners will have a financial incentive to take care in how they use their robots, since they could suffer higher premiums through the loss of their no-claims bonuses.

In order to enforce mandatory robot insurance requirements on the owner of a robot, there will need to be heavy legal sanctions against owners and/or operators of robots who are not adequately insured or who are not insured at all, but who have somehow managed to bypass the disabling technology in their robot’s black box. If a clever computer expert manages to hack into the robot’s insurance renewal software and enable an uninsured robot to be used, they will be committing a criminal offence in the same way that car drivers in most jurisdictions are committing an offence when they drive without adequate insurance cover. The robot’s black box, while monitoring the status of the owner’s insurance policy, could transmit an alert message to the appropriate regulatory authorities, advising that an uninsured robot is in use, or an uninsured modification to an already insured robot, together with the owner’s name and contact details. The automatic generation of penalty notices for certain motoring offences is already commonplace, so a similar scheme for uninsured robots seems eminently reasonable, and in the most serious cases a message transmitted to the police to assist them in identifying and tracking down errant robot owners.

In the case of motor insurance, in many jurisdictions there are some types of vehicle that are deemed not to be motor vehicles for the purposes of insurance requirements. In the UK this includes lawnmowers, and some electrically assisted pedal bikes. These exclusions provide a model that can readily be extended to robot insurance. Some toy robots designed for children, for example, will not need to be insured because the risk of serious injury or death being caused by such a toy is very slight, and warning labels can easily be affixed to the toy to cover such possibilities as swallowing removable parts.

One challenge to a system such as I propose is presented by consumers who, after their initial purchase, subsequently buy hardware or software add-ons that affect the risks posed by their robot. In order to cater for these possible dangers a robot’s software could be programmed to detect any such add-ons and send an electronic message to the insurer’s “actuary” – a piece of software rather than a human actuary – which would then calculate the appropriate change in premium, and the owner would be informed accordingly. Even more dangerous could be robot enthusiasts who possess the technical knowhow to modify their robots in all sorts of ways, again creating the possibility of an increased risk, by turning an innocuous robot into a dangerous one. In such cases the robot’s owner would be compelled by its black box to self-authenticate by filling out an electronic form with details of the modification, in order that an appropriate increase in insurance premium could be calculated. An owner who is found to have given false information regarding their modification would be liable to prosecution in the same way as a motorist who gives false information on the application form for a motor insurance policy.” (Levy, 2012)