ISY1000 Report: Ethical and Professional Practice in Self-Driving Cars

This report delves into the ethical and professional implications of self-driving cars, addressing key issues such as liability in accidents, the impact of AI algorithms, and the automotive industry's response to standardization. It examines the levels of automation and their effect on liability, highlighting that manufacturers are liable in higher automation levels. The report discusses the impact on the insurance industry, predicting a drop in premiums and potential challenges. It explores the pros and cons of standard AI algorithms, the reaction of manufacturers, and the need for increased care in developing vehicle software. The report concludes with recommendations for developers to incorporate ethical settings, emphasizing the promising future of autonomous vehicles and their potential to reduce accidents compared to human drivers.

Professional and Ethical Practice
Student’s Name
Institutional Affiliation

INTRODUCTION
• A report by the National Highway Traffic Safety Administration (NHTSA) note that
most car accidents in the roads is as a result of speeding, distracted drivers and drunk
driving.
• Human errors are responsible for more than 90% of the car accidents could be
essentially eradicated with self-driving cars (Ramsey, 2015).
• Self-driving cars are skilled to make decision in regards to when to break as well as
where to steer using particular artificial intelligence which is committed to achieving
a narrow task (Goodall, 2014).

Where does liability reside when self-driving cars are involved an accident?
• In case a self-driving car is involved in an accident where the liability reside will
depend on the automation level of the car that is involved in the accident.
• There are several levels of automation for self-driving cars, hence it the self-
driving car fall under the first 3 automotive levels the liability will fall to human
driver.
• If the self-driving car is for automotive level 4 or 5 the the manufacturer will be
liable

Impact of development of self-driving cars to
the insurance industry
• Liability will be assumed by automakers
• Drop in insurance premiums because accidents will become rare.
• Struggle by the insurance industry because more drivers will reduce or drop
coverage

Cont’
Liability will be assumed by automakers: In case an accident occurs without the
involvement of a human driver, the manufacturer is the responsible for the damages.
Drop in insurance premiums because accidents will become rare: Experts have
predicted that with self-driving vehicles becoming the novel norm, it will result in a
drop in accidents.
Struggle by the insurance industry because more drivers will reduce or drop
coverage: The advancements in autonomous vehicles will reach a point where
drivers will not realize the need to carry personal accident insurance.

Pros of AI algorithms as standard across
automobile manufacturers
• Massive increase supports the usage of artificial intelligence systems in cars could
have to standard across the autonomous vehicle applications.
• Deep learning is the main application in the automotive industry that comprises
computer perception and vision.
• Standard AI algorithms in the vehicle manufacturing industry is necessary to
allow for a system that lower tolerance to mistakes and capability to easily isolate
errors.

Cons of AI algorithms as standard across automobile manufacturers
• Deep learning faces a number of criticism.
• To begin with dee learning generalizes scenarios at the time of training which is
doubtful hence calls for through investigation.
• Standard AI systems have a problem with extremely solid geometrical basis that
theoretically can be resolved more efficiently through other approaches (Herman
& Ismail, 2017).

Reaction of manufacturers to standardization of automobile AI algorithms
• Solid relationships with OEMs automobile manufacturers are ready to take
proactive roles in advanced drive-assistance systems (ADAS) development.
• The automotive industry taking charge of ADAS development it will ensure that
OEMs has the opportunity to differentiate their selves from rivals for autonomous-
driving and driver support functions.

Response to whether the degree of care
exercised in developing vehicle software
should increase with level of autonomy
• All vehicle software should not be treated with the same level of care because
they these automotive levels are develop to realize a specific objective in the
autonomous development lifecycle (Casey & Niblett, 2016).

Conclusion
• The future of autonomous cars is exciting and promising because these vehicles
have the ability to pay attention unlike human drivers who can be distracted or
drive under influence of alcohol and other drugs leading to accidents.

Recommendations
• The developers of self-driving developers should include both mandatory and
personal ethics settings which allows the user to choose the ethical preferences s
for their vehicle to help solve the responsibility problem.

References
• Borenstein, J., Herkert, J. R., & Miller, K. W. (2019). Self-driving cars and engineering ethics: the need for a system level
analysis. Science and engineering ethics, 25(2), 383-398. https://link.springer.com/article/10.1007/s11948-017-0006-0
• Bringsjord, S., & Sen, A. (2016). On creative self-driving cars: Hire the computational logicians, fast. Applied Artificial
Intelligence, 30(8), 758-786.
• Casey, A. J., & Niblett, A. (2016). Self-driving laws. University of Toronto Law Journal, 66(4), 429-442.
• Fleetwood, J. (2017). Public health, ethics, and autonomous vehicles. American journal of public health, 107(4), 532-537.
• Goodall, N. J. (2014). Machine ethics and automated vehicles. In Road vehicle automation (pp. 93-102). Springer, Cham.
• Herman, S., & Ismail, K. (2017). Single Camera Object Detection for Self-Driving Vehicle: A Review. Journal of the Society of
Automotive Engineers Malaysia, 1(3).
• Mackie, T. (2018). Proving liability for highly and fully automated vehicle accidents in Australia. Computer Law & Security
Review, 34(6), 1314-1332. Mackie, T. (2018). Proving liability for highly and fully automated vehicle accidents in Australia. Computer
Law & Security Review, 34(6), 1314-1332. https://www.sciencedirect.com/science/article/pii/S026736491830356X
• Nyholm, S., & Smids, J. (2016). The ethics of accident-algorithms for self-driving cars: An applied trolley problem? Ethical theory
and moral practice, 19(5), 1275-1289.
• Ramsey, M. (2015). Self-driving cars could cut down on accidents, study says. Report predicts mass adoption of auto-piloted vehicles
beginning in about 15 years. The Wall Street Journal, 5.
• Scheutz, M. (2016). The need for moral competency in autonomous agent architectures. In Fundamental issues of artificial
intelligence (pp. 517-527). Springer, Cham.