Unit 5: Ethics and Technology Flashcards

Explain the impacts technology and artificial intelligence have, from an ethical perspective, on the banking and financial services industry.

1
Q

What is an algorithm?

A

A procedure or formula for solving a problem, based on conducting a sequence of specified actions. It can therefore be described as a process,based on rules, that if followed solves a problem or produces a decision.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is a moral agent?

A

A ‘being’ who has the ability to discern right from wrong.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Can a machine be an agent?

A

No.
An agent is being who has the ability to
discern right from wrong. Machines cannot make these decisions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

How can moral agents make decisions?

A

They can make a considered judgment based on professional experience, seek further information or gain a second opinion.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What moral responsibility do moral agents have?

A

To not cause deliberate and unjustified harm

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Traditionally, who is moral agency assigned to?

A

Only to those who can be held responsible for
their actions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Why should we expect people to act as moral agents?

A

By expecting people to act as moral agents, we hold them accountable for the harm they cause others.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

When are we morally responsible?

A

If:
* We are causally responsible for the effects (or lack of effects) of our actions or inactions.
* We intentionally brought about the effects or could have foreseen them.
* The effects are morally important.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

If someone accidentally causes harm to someone else, will they still be regarded as morally responsible?

A

They can be, but we could consider them less blameworthy because it was not intentional.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a machine learning algorithm?

A

Machine learning algorithms are a specific kind of algorithm which ‘learn’ their own ways of analysing data and reaching decisions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

How is big data used by banks?

A

Big data is a term used to describe extremely large sets of data that can be analysed by computers to reveal patterns and trends, especially in relation to human behaviours,
decisions and interactions.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are key ethical concepts related to data analysis?

A

Privacy and consent

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

When dealing with personal data from which people can be identified, what provisions must organisations comply with?

A

Australian Privacy Principles (APPs).

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What do the Australian Privacy Principles (APPs) set out?

A

The rights and data subjects and the obligations of organisations
which collect, process, analyse, use and store personal data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What two elements are needed to build an algorithm?

A
  1. Data (what happened in the past).
  2. A definition of success (what we’re looking for which becomes embedded in the code).
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

How can autonomous algorithms express bias?

A

Data can represent historical bias, as can the criteria for success, which is often based on opinion.

17
Q

What are ethical problems algorithms have that human agents do not have?

A

Decisions made by algorithms are considered objective, but the reasons behind their decisions are not transparent. There is little room to appeal the decision. See below for more:

  1. They make bias appear objective (can can cement social biases they reflect).
  2. Decisions resulting from algorithms are not transparent - we can ask humans to defend their decisions, but when an algorithm makes a decision the exact processes and calculations that went into that decision are not available to the person at the other end of that decision.