6.3 Ethical Dilemmas Flashcards
Ethical dilemma
In a situation thinking what is the right thing to do.
Involves deciding between lots if different things which are all right for different reasons.
Kidders four ethical conflicts
- truth vs loyalty
- individual vs community
- short term vs long term
- justice vs mercy
Trust vs loyalty
Example: saying the truth about the colleagues saying what they did was wrong OR telling a lie to support the colleague
Honesty vs promise keeping
Individual vs community
Example: taking leave whilst it is busy at work OR postponing the holiday to help your team from having to work longer hours
Short term vs long term
Example: accepting a profitable loan to a company who wants to finance OR declining the loan because will add to fossil fuel emissions.
Desire vs future goals
Justice vs mercy
Fairness, equity vs empathh and compassion.
Example: applying regulation to punish an employee for wrongdoing OR leave it because the employee has mitigating circumstances
How to decide what action to take
What is the most right thing to do?
- considering any laws or regulation as always have to comply with the law
- assessing the consequences of each choice and how they will affect the bank, the people involved etc
- look at the actions and see for yourself if you will willing take that.
- choose the one that has the lease amount of negative impact
Open banking
Banks share customers data and was given consent to do this.
Make it easier and quicker for the customer to change banks and manage their affairs.
Customers can see details of all their banks account in one place
Algorithms
Can assess loan applications faster and more accurately.
Chatbox help advice customers
Artificial intelligence (AI) - process information rapidly
New technology
All allows customers to benefit from a quick easy and seamless Banking experience
This can lead to increase customer satisfaction and loyalty
Algorithms
Formula used by a computer in calculations for solving a problem.
Is used to make quick decisions based on a lot of data .
Banking professionals make better marketing , risk and financial decisions.
Can’t blame the machine if wrong decisions are made (not responsible) machine is not a professional
Machine bias
Human build the algorithms and provide the data.
Machine decisions can therefore be biased.
Machine bias is based on mathematics so hard to find a solution.
The customer cannot be given details of the calculations that underlie the machines decision as they will not understand them.
Can be insulting to a customer who may feel that their financial well-being it’s not worth the attention of another human being .
Legal protection of automated decision making
In EU, GDPR gives individuals rights regarding automated decisions.
(Decisions made without any human involvement).
GDPR has rules to protect individuals where decisions are based on automated processes.
The general date protection regulation. (GDPR)
Sets out protection for individuals in respect of data in the EU and UK.
Other countries have data protection laws.
Banks must:
- Informed the individual about the automated decision-making
- Give the individual the right to have the automated decision reviewed by a person
- Give the individual the opportunity to argue against the automated decision.
