Moral Dilemma Analysis of AI Application in Insurance
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AI Summary
This article analyzes the ethical considerations of using AI in the insurance industry, including the legal aspects, fairness of the activity, and personal reflection. It discusses the benefits and harms of AI application in insurance and emphasizes the need for ethical decision-making.
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Running head: MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Name of the Student
Name of the University
Author Note
Introduction
MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Name of the Student
Name of the University
Author Note
Introduction
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1MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Application of Artificial intelligence or AI technology has various benefits. It automates
decision regarding providing insurance to individuals according to their requirements. It also
provides automatic quotation for insurance package, which is also customisable according to the
needs of the consumer.
Discussion:
Ethical decision-making framework:
The framework chosen for the ethical analysis is The Blanchard-Peale Framework. It is a
simple and effective framework for deciding if an action is ethical or not. It consists of three
component for ethical analysis. These components are:
Legal aspect of activity: When an activity is conducted, it should be analysed from legal
framework. An activity needs to be consistent with relevant rules and regulations before it is
considered as ethical. This is one of the first and most important aspect of any ethical analysis
according to this framework.
Fairness of activity: While doing any activity it is important to identify if individual has been
honest or not while conducted any activity. Action has to be honest and fair with respect to
interest of larger entity. If this is not achieved, the action is not ethical.
Personal realization for activity: Personal reflection on any activity is important to identify
and analyse ethical issue associated with an activity.
This framework is applied to analyse important ethical consideration required for IS professional
to consider while designing health insurance policy.
Legal aspect of activity:
Application of Artificial intelligence or AI technology has various benefits. It automates
decision regarding providing insurance to individuals according to their requirements. It also
provides automatic quotation for insurance package, which is also customisable according to the
needs of the consumer.
Discussion:
Ethical decision-making framework:
The framework chosen for the ethical analysis is The Blanchard-Peale Framework. It is a
simple and effective framework for deciding if an action is ethical or not. It consists of three
component for ethical analysis. These components are:
Legal aspect of activity: When an activity is conducted, it should be analysed from legal
framework. An activity needs to be consistent with relevant rules and regulations before it is
considered as ethical. This is one of the first and most important aspect of any ethical analysis
according to this framework.
Fairness of activity: While doing any activity it is important to identify if individual has been
honest or not while conducted any activity. Action has to be honest and fair with respect to
interest of larger entity. If this is not achieved, the action is not ethical.
Personal realization for activity: Personal reflection on any activity is important to identify
and analyse ethical issue associated with an activity.
This framework is applied to analyse important ethical consideration required for IS professional
to consider while designing health insurance policy.
Legal aspect of activity:
2MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Application of AI in providing insurance policy has various benefits, it Automates decision
regarding health insurance claim and helps in payment adjustment. It create a strong portfolio in
the market for the company. Along with that, company will have competitive and strategic
advantage over traditional insurance provider, which is a long-term benefit for the company. For
individual staff the benefits include customers efficiently through integration of chatbots,
automate decision regarding insurance claim, and manage payments and other technical aspect of
the service. As company grow with their service through effective business process, it will
benefit staff of the company in long term. The business clients will be benefitted from this
technology as well. Artificial intelligence helps them avoiding fraud in insurance settlement and
get price quote for insurance faster. In addition, concerning industry, it provides context for
innovation and enrich industry with application of technology. Along with benefits, it has some
drawbacks as well, not only for the organization who is providing insurance policy, but also for
all the entities considered in the ethical framework.
According to data protection regulation, if data is collected about individuals specially critical
information like health data, it has to be protected. If data collected for this purpose is hacked, it
will bring legal action against the company. Too much dependence on technology might affects
skills of the employee in long terms, application of AI might bring threat to traditional insurance
provider, and this might affect the industry itself in long term.
Various sophisticated tools are available for exploiting data security and this has to be considered
for data security as well. It is not enough to only consider that data collection is legal, it is also s
to secure these data as well for ensuring that data is secured. Hence, after collecting data for
automation with AI technology, these data has to be encrypted. Once data is encrypted, it is
difficult to access this data. Hence, data after collecting from individuals needs to be stored in
secure place.
For applying data in automation through AI, it is important to ensure that data is accessible from
anywhere. Hence data needs to be stored in the cloud. for this private cloud technology has to be
considered which ensures that data is not shared between others. These aspects are important too
for enhancing data security and data processing.
IS professionals will have to take this consideration into account while collecting data for
providing health insurance and designing health insurance policy.
Fairness of activity:
While applying AI, it is important to analyse benefits for analysing fairness of this action and
this is an important consideration for IS professionals.
Benefits of this action:
Application of AI in providing insurance policy has various benefits, it Automates decision
regarding health insurance claim and helps in payment adjustment. It create a strong portfolio in
the market for the company. Along with that, company will have competitive and strategic
advantage over traditional insurance provider, which is a long-term benefit for the company. For
individual staff the benefits include customers efficiently through integration of chatbots,
automate decision regarding insurance claim, and manage payments and other technical aspect of
the service. As company grow with their service through effective business process, it will
benefit staff of the company in long term. The business clients will be benefitted from this
technology as well. Artificial intelligence helps them avoiding fraud in insurance settlement and
get price quote for insurance faster. In addition, concerning industry, it provides context for
innovation and enrich industry with application of technology. Along with benefits, it has some
drawbacks as well, not only for the organization who is providing insurance policy, but also for
all the entities considered in the ethical framework.
According to data protection regulation, if data is collected about individuals specially critical
information like health data, it has to be protected. If data collected for this purpose is hacked, it
will bring legal action against the company. Too much dependence on technology might affects
skills of the employee in long terms, application of AI might bring threat to traditional insurance
provider, and this might affect the industry itself in long term.
Various sophisticated tools are available for exploiting data security and this has to be considered
for data security as well. It is not enough to only consider that data collection is legal, it is also s
to secure these data as well for ensuring that data is secured. Hence, after collecting data for
automation with AI technology, these data has to be encrypted. Once data is encrypted, it is
difficult to access this data. Hence, data after collecting from individuals needs to be stored in
secure place.
For applying data in automation through AI, it is important to ensure that data is accessible from
anywhere. Hence data needs to be stored in the cloud. for this private cloud technology has to be
considered which ensures that data is not shared between others. These aspects are important too
for enhancing data security and data processing.
IS professionals will have to take this consideration into account while collecting data for
providing health insurance and designing health insurance policy.
Fairness of activity:
While applying AI, it is important to analyse benefits for analysing fairness of this action and
this is an important consideration for IS professionals.
Benefits of this action:
3MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
1. for organizations:
Short Term: Automates decision regarding health insurance claim and payment
adjustment
Medium/ Long Term : create a strong portfolio in the market with competitive and
strategic advantage over traditional insurance provider
2. for individuals:
Short Term: Increase their workflow through automation
Medium/ Long Term : Opportunities for growth as company grow
3. for business clients:
Short Term: Reduction in fraud regarding insurance claim
4. for industry:
Medium/ Long Term : Allows innovation in the industry
Harm caused by this action
Medium/ Long Term : if data stored for providing service is stolen company have to deal
with legal consequences and legal actions
Short Term: Data might be hacked
Medium/ Long Term: employees might be too much dependent on technology and might
affect their skills and productivity as well. Automation might reduce human workforce as
well.
Medium/ Long Term : might not get insurance when required
Short Term: No harms for the public
Medium/ Long Term : Traditional insurance providers will increased competition which
might result in reduction in insurance companies
1. for organizations:
Short Term: Automates decision regarding health insurance claim and payment
adjustment
Medium/ Long Term : create a strong portfolio in the market with competitive and
strategic advantage over traditional insurance provider
2. for individuals:
Short Term: Increase their workflow through automation
Medium/ Long Term : Opportunities for growth as company grow
3. for business clients:
Short Term: Reduction in fraud regarding insurance claim
4. for industry:
Medium/ Long Term : Allows innovation in the industry
Harm caused by this action
Medium/ Long Term : if data stored for providing service is stolen company have to deal
with legal consequences and legal actions
Short Term: Data might be hacked
Medium/ Long Term: employees might be too much dependent on technology and might
affect their skills and productivity as well. Automation might reduce human workforce as
well.
Medium/ Long Term : might not get insurance when required
Short Term: No harms for the public
Medium/ Long Term : Traditional insurance providers will increased competition which
might result in reduction in insurance companies
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4MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
The AI has been helping enormously in the insurance industry. The use of AI in the healthcare
industry has been helping in gathering health related data. These data are of great importance for
the insurance providers to decide about credibility of an individual to claim for insurance term.
Fraud in insurance claim has been one of the critical problem in insurance industry and it
becomes difficult for policy makers to ensure fraud free insurance claim. However, application
of AI provides context for resolving these issues properly. People like to have insurance in less
time and without any fraud, for which AI is an important consideration. However when new
services are brought to the market it is important to review applicable rules and regulation and
analyse business process about ethical framework. Hence, in this context, application of AI in
providing insurance policies is analysed with ethical framework with detailed analysis of
possible benefits and harms of this application both in short-term and mid to long term context
for providing a comprehensive overview on ethical analysis.
The use of the artificial intelligence in insurance industry might be harmful for the employees as
there might be some data loss of patients in the hospitals. These issues have to be considered by
the IS professionals. If the technology has been universalized, the use of the technology will be
done by every clients in the market. Therefore, thus become an issue for the organzation and
professionals to handle the situation. The hackers might target insurance organization for
breaching into their network server and database if the organization. This has been causing a
huge data loss to the organization in the healthcare industry. The use of AI in the insurance
industry has been maintaining a keen approach in the market. Management might problems in
defending their data in case there have been universalization of technology. This technology
need to be secure properly that might help in providing a proper approach to the development of
industry.
Personal realization for activity:
Before initial implementation of AI in the healthcare system, there is a need to provide proper
training by feeding in data generated through clinical activities like screening. They help the
process of AI to expand in its use in the healthcare sector regarding allowance for insurance.
Company has more power over employees, clients and the public regarding choice of their action
and it is duty of the company to ensure that their action are consistent with ethical framework.
The rights have not been violating because of their actions it cannot be used in end user for
violating rights of staff’s and patients. The organization has been following all the policies that
are maintaining a keen approach in the insurance industry. The policies and legal frameworks of
the organization has been properly followed. Introduction of AI in insurance have brought about
numerous benefits and it has rapidly increased the progress report of the allowance of insurance ,
providing status regarding insurance claim. The insurance system by using the applications of
AI has reduced the turnaround in providing insurance. AI is applied in both structured and
unstructured healthcare data. Machine learning methodologies are used to get network data and
The AI has been helping enormously in the insurance industry. The use of AI in the healthcare
industry has been helping in gathering health related data. These data are of great importance for
the insurance providers to decide about credibility of an individual to claim for insurance term.
Fraud in insurance claim has been one of the critical problem in insurance industry and it
becomes difficult for policy makers to ensure fraud free insurance claim. However, application
of AI provides context for resolving these issues properly. People like to have insurance in less
time and without any fraud, for which AI is an important consideration. However when new
services are brought to the market it is important to review applicable rules and regulation and
analyse business process about ethical framework. Hence, in this context, application of AI in
providing insurance policies is analysed with ethical framework with detailed analysis of
possible benefits and harms of this application both in short-term and mid to long term context
for providing a comprehensive overview on ethical analysis.
The use of the artificial intelligence in insurance industry might be harmful for the employees as
there might be some data loss of patients in the hospitals. These issues have to be considered by
the IS professionals. If the technology has been universalized, the use of the technology will be
done by every clients in the market. Therefore, thus become an issue for the organzation and
professionals to handle the situation. The hackers might target insurance organization for
breaching into their network server and database if the organization. This has been causing a
huge data loss to the organization in the healthcare industry. The use of AI in the insurance
industry has been maintaining a keen approach in the market. Management might problems in
defending their data in case there have been universalization of technology. This technology
need to be secure properly that might help in providing a proper approach to the development of
industry.
Personal realization for activity:
Before initial implementation of AI in the healthcare system, there is a need to provide proper
training by feeding in data generated through clinical activities like screening. They help the
process of AI to expand in its use in the healthcare sector regarding allowance for insurance.
Company has more power over employees, clients and the public regarding choice of their action
and it is duty of the company to ensure that their action are consistent with ethical framework.
The rights have not been violating because of their actions it cannot be used in end user for
violating rights of staff’s and patients. The organization has been following all the policies that
are maintaining a keen approach in the insurance industry. The policies and legal frameworks of
the organization has been properly followed. Introduction of AI in insurance have brought about
numerous benefits and it has rapidly increased the progress report of the allowance of insurance ,
providing status regarding insurance claim. The insurance system by using the applications of
AI has reduced the turnaround in providing insurance. AI is applied in both structured and
unstructured healthcare data. Machine learning methodologies are used to get network data and
5MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
neural language is for the unstructured data. In case of other chronic diseases AI helps in easy
identification of the patient’s condition. This information is important to collect for providing
insurance. If action is universalized benefits for the organization is that it need stronger
innovation for service and thus provide context for innovation. if action is universalized harm
for the organization is that Management will not be able to manger employees
If action is universalized contradiction for the organization is that it Might cause the end of
company
with more power comes greater responsibility and in reference to this, it is also duty of the
company to ensure that they protects rights of their consumers, clients and public as they are
powerless compared to the company. The actions might violate the rights of patients in case of
universalization of AI technology in the insurance industry.
employees should realise that it is not only the organization that is responsible for data security
collected for providing health insurance. Employees need to ensure that data is collected properly
and also stored appropriately so that it is not exploited. If an employee wants to ensure that
action is ethical, he or she should reflect personally that even though illegal access or share of
data might benefit company, it might compromise security of personals. They have to think from
this framework, not just from organisational and business context. this will help them to analyse
ethical issues through personal reflection and this will also help them to design policy that is
consistent with ethical framework.
Summary
Framewo
rk
The
Organizat
ion selling
products/
services
Individua
l Staff
The
Organizatio
n’s business
Clients
The Public The
Industry/
Professio
n
Ethical?
Benefits
of this
action?
ST : Yes
LT : Yes
ST : No
LT : Yes
ST : Yes
LT : No
ST : N/A
LT : N/A
ST : No
LT : Yes
Unethical
Harm ST : No ST : Yes ST : No ST : N/A ST : No
neural language is for the unstructured data. In case of other chronic diseases AI helps in easy
identification of the patient’s condition. This information is important to collect for providing
insurance. If action is universalized benefits for the organization is that it need stronger
innovation for service and thus provide context for innovation. if action is universalized harm
for the organization is that Management will not be able to manger employees
If action is universalized contradiction for the organization is that it Might cause the end of
company
with more power comes greater responsibility and in reference to this, it is also duty of the
company to ensure that they protects rights of their consumers, clients and public as they are
powerless compared to the company. The actions might violate the rights of patients in case of
universalization of AI technology in the insurance industry.
employees should realise that it is not only the organization that is responsible for data security
collected for providing health insurance. Employees need to ensure that data is collected properly
and also stored appropriately so that it is not exploited. If an employee wants to ensure that
action is ethical, he or she should reflect personally that even though illegal access or share of
data might benefit company, it might compromise security of personals. They have to think from
this framework, not just from organisational and business context. this will help them to analyse
ethical issues through personal reflection and this will also help them to design policy that is
consistent with ethical framework.
Summary
Framewo
rk
The
Organizat
ion selling
products/
services
Individua
l Staff
The
Organizatio
n’s business
Clients
The Public The
Industry/
Professio
n
Ethical?
Benefits
of this
action?
ST : Yes
LT : Yes
ST : No
LT : Yes
ST : Yes
LT : No
ST : N/A
LT : N/A
ST : No
LT : Yes
Unethical
Harm ST : No ST : Yes ST : No ST : N/A ST : No
6MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
caused by
this
action?
LT : Yes LT : Yes LT : Yes
LT : N/A
LT : Yes
Benefits if
action is
universali
zed?
No No No No No Unethical
Harm if
action is
universali
sed?
Yes Yes Yes Yes Yes
Contradic
tion if
universali
sed?
Yes Yes Yes Yes Yes Unethical
Used as
means to
end,
violating
their
rights?
N/A Yes Yes Yes No Unethical
caused by
this
action?
LT : Yes LT : Yes LT : Yes
LT : N/A
LT : Yes
Benefits if
action is
universali
zed?
No No No No No Unethical
Harm if
action is
universali
sed?
Yes Yes Yes Yes Yes
Contradic
tion if
universali
sed?
Yes Yes Yes Yes Yes Unethical
Used as
means to
end,
violating
their
rights?
N/A Yes Yes Yes No Unethical
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7MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Violating
rights,
seen as
unjust (to
powerless
), action
taker has
more
power?
N/A Yes Yes Yes N/A Unethical
Conclusion
Though AI will automate the process of decision making regarding health insurance, the
choice of decision still depends on the company itself. Things like collecting data of users
without their acknowledgement, breaching consumer trust over insurance policy are some of the
important ethical issue that needs to be considered for developing an ethical and effective
integration of artificial intelligence in insurance industry for providing faster and fraud free
insurance policy.
Violating
rights,
seen as
unjust (to
powerless
), action
taker has
more
power?
N/A Yes Yes Yes N/A Unethical
Conclusion
Though AI will automate the process of decision making regarding health insurance, the
choice of decision still depends on the company itself. Things like collecting data of users
without their acknowledgement, breaching consumer trust over insurance policy are some of the
important ethical issue that needs to be considered for developing an ethical and effective
integration of artificial intelligence in insurance industry for providing faster and fraud free
insurance policy.
8MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
References
Abrahám, A., de Sousa, J.B., Marimon, R. and Mayr, L., 2017. On the design of a European
unemployment insurance mechanism. Draft, European University Institute, Florence.
Adem, A. and Dağdeviren, M., 2016. A life insurance policy selection via hesitant fuzzy
linguistic decision making model. Procedia Computer Science, 102, pp.398-405.
Alabi, A.N., Onuoha, F.M., Madaki, A.J., Nwajei, A.I., Uwakwem, A.C. and Alabi, K.M., 2017.
Enrolees Perception of the Merits and Demerits of National Health Insurance Scheme in a
Nigerian Tertiary Health Facility.
Balasubramanian, R., Libarikian, A. and McElhaney, D., 2018. Insurance 2030—The impact of
AI on the future of insurance. McKinsey & Company, New York, NY, USA, Apr.
Bauer, M., Glenn, T., Monteith, S., Bauer, R., Whybrow, P.C. and Geddes, J.,. Ethical
perspectives on recommending digital technology for patients with mental illness. International
journal of bipolar disorders, 5(1), (2017), p.6.
Berendt, B., Büchler, M. and Rockwell, G., 2015. Is it research or is it spying? Thinking-through
ethics in Big Data AI and other knowledge sciences. KI-Künstliche Intelligenz, 29(2), pp.223-
232.
Brundage, M. and Bryson, J., 2016. Smart Policies for Artificial Intelligence. arXiv preprint
arXiv:1608.08196.
Crigger, E. and Khoury, C., 2019. Making policy on augmented intelligence in health care. AMA
journal of ethics, 21(2), pp.188-191.
Goolsbee, A., 2018. Public policy in an AI economy (No. w24653). National Bureau of
Economic Research.
References
Abrahám, A., de Sousa, J.B., Marimon, R. and Mayr, L., 2017. On the design of a European
unemployment insurance mechanism. Draft, European University Institute, Florence.
Adem, A. and Dağdeviren, M., 2016. A life insurance policy selection via hesitant fuzzy
linguistic decision making model. Procedia Computer Science, 102, pp.398-405.
Alabi, A.N., Onuoha, F.M., Madaki, A.J., Nwajei, A.I., Uwakwem, A.C. and Alabi, K.M., 2017.
Enrolees Perception of the Merits and Demerits of National Health Insurance Scheme in a
Nigerian Tertiary Health Facility.
Balasubramanian, R., Libarikian, A. and McElhaney, D., 2018. Insurance 2030—The impact of
AI on the future of insurance. McKinsey & Company, New York, NY, USA, Apr.
Bauer, M., Glenn, T., Monteith, S., Bauer, R., Whybrow, P.C. and Geddes, J.,. Ethical
perspectives on recommending digital technology for patients with mental illness. International
journal of bipolar disorders, 5(1), (2017), p.6.
Berendt, B., Büchler, M. and Rockwell, G., 2015. Is it research or is it spying? Thinking-through
ethics in Big Data AI and other knowledge sciences. KI-Künstliche Intelligenz, 29(2), pp.223-
232.
Brundage, M. and Bryson, J., 2016. Smart Policies for Artificial Intelligence. arXiv preprint
arXiv:1608.08196.
Crigger, E. and Khoury, C., 2019. Making policy on augmented intelligence in health care. AMA
journal of ethics, 21(2), pp.188-191.
Goolsbee, A., 2018. Public policy in an AI economy (No. w24653). National Bureau of
Economic Research.
9MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
Iyengar, A., Kundu, A. and Pallis, G.,. Healthcare Informatics and Privacy. IEEE Internet
Computing, 22(2), (2018), pp.29-31.
Jaremko, J.L., Azar, M., Bromwich, R., Lum, A., Cheong, L.H.A., Gibert, M., Laviolette, F.,
Gray, B., Reinhold, C., Cicero, M. and Chong, J., 2019. Canadian Association of Radiologists
White Paper on Ethical and Legal Issues Related to Artificial Intelligence in
Radiology. Canadian Association of Radiologists Journal.
Jing, L., Zhao, W., Sharma, K. and Feng, R., 2018, January. Research on Probability-based
Learning Application on Car Insurance Data. In 2017 4th International Conference on
Machinery, Materials and Computer (MACMC 2017). Atlantis Press.
Kang, S. and Song, J., 2018. Feature selection for continuous aggregate response and its
application to auto insurance data. Expert Systems with Applications, 93, pp.104-117.
Lamberton, C., Brigo, D. and Hoy, D., 2017. Impact of Robotics, RPA and AI on the insurance
industry: challenges and opportunities. Journal of Financial Perspectives, 4(1).
Montag, C. and Elhai, J.D., 2019. A new agenda for personality psychology in the digital
age?. Personality and Individual Differences, 147, pp.128-134.
Mousa, A.S., Pinheiro, D. and Pinto, A.A., 2016. Optimal life-insurance selection and purchase
within a market of several life-insurance providers. Insurance: Mathematics and Economics, 67,
pp.133-141.
Nakano, Y., 2016. On a law of large numbers for insurance risks. arXiv preprint
arXiv:1601.03171.
O'sullivan, S., Nevejans, N., Allen, C., Blyth, A., Leonard, S., Pagallo, U., Holzinger, K.,
Holzinger, A., Sajid, M.I. and Ashrafian, H., 2019. Legal, regulatory, and ethical frameworks for
Iyengar, A., Kundu, A. and Pallis, G.,. Healthcare Informatics and Privacy. IEEE Internet
Computing, 22(2), (2018), pp.29-31.
Jaremko, J.L., Azar, M., Bromwich, R., Lum, A., Cheong, L.H.A., Gibert, M., Laviolette, F.,
Gray, B., Reinhold, C., Cicero, M. and Chong, J., 2019. Canadian Association of Radiologists
White Paper on Ethical and Legal Issues Related to Artificial Intelligence in
Radiology. Canadian Association of Radiologists Journal.
Jing, L., Zhao, W., Sharma, K. and Feng, R., 2018, January. Research on Probability-based
Learning Application on Car Insurance Data. In 2017 4th International Conference on
Machinery, Materials and Computer (MACMC 2017). Atlantis Press.
Kang, S. and Song, J., 2018. Feature selection for continuous aggregate response and its
application to auto insurance data. Expert Systems with Applications, 93, pp.104-117.
Lamberton, C., Brigo, D. and Hoy, D., 2017. Impact of Robotics, RPA and AI on the insurance
industry: challenges and opportunities. Journal of Financial Perspectives, 4(1).
Montag, C. and Elhai, J.D., 2019. A new agenda for personality psychology in the digital
age?. Personality and Individual Differences, 147, pp.128-134.
Mousa, A.S., Pinheiro, D. and Pinto, A.A., 2016. Optimal life-insurance selection and purchase
within a market of several life-insurance providers. Insurance: Mathematics and Economics, 67,
pp.133-141.
Nakano, Y., 2016. On a law of large numbers for insurance risks. arXiv preprint
arXiv:1601.03171.
O'sullivan, S., Nevejans, N., Allen, C., Blyth, A., Leonard, S., Pagallo, U., Holzinger, K.,
Holzinger, A., Sajid, M.I. and Ashrafian, H., 2019. Legal, regulatory, and ethical frameworks for
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10MORAL DILEMMA ANALYSIS OF AI APPLICATION IN INSURANCE
development of standards in artificial intelligence (AI) and autonomous robotic surgery. The
International Journal of Medical Robotics and Computer Assisted Surgery, 15(1), p.e1968.
Pesapane, F., Volonté, C., Codari, M. and Sardanelli, F., 2018. Artificial intelligence as a
medical device in radiology: ethical and regulatory issues in Europe and the United
States. Insights into imaging, 9(5), pp.745-753.
Ruß, J., 2018. Asymmetric Information in Secondary Insurance Markets: Evidence from the Life
Settlement Market.
development of standards in artificial intelligence (AI) and autonomous robotic surgery. The
International Journal of Medical Robotics and Computer Assisted Surgery, 15(1), p.e1968.
Pesapane, F., Volonté, C., Codari, M. and Sardanelli, F., 2018. Artificial intelligence as a
medical device in radiology: ethical and regulatory issues in Europe and the United
States. Insights into imaging, 9(5), pp.745-753.
Ruß, J., 2018. Asymmetric Information in Secondary Insurance Markets: Evidence from the Life
Settlement Market.
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