18 - From data-driven to AI-driven

Question 1

What is the final stage of data transformation in a business?

Answer 1

To become a leader and innovator, capable of systematically outperforming competitors.

Question 2

How does artificial intelligence improve decision-making?

Answer 2

AI can improve decision-making beyond the capabilities of the people in the business.

Question 3

What does the data team focus on in the final stage of transformation?

Answer 3

Providing data products that the business uses to thrive.

Question 4

What are the three activities in the VBI model for this wave?

Answer 4

• Value
• Build
• Improve

Question 5

What does the ‘Value’ aspect of the VBI model focus on?

Answer 5

Expressing the value of data in innovation and creativity.

Question 6

What is emphasized in the ‘Build’ aspect of the VBI model?

Answer 6

Applying AI to strategic, future-facing processes.

Question 7

What is the key focus of the ‘Improve’ aspect in the VBI model?

Answer 7

Creating mechanisms for innovation to become business as usual.

Question 8

Fill in the blank: Artificial intelligence may create profound insights from data and exceed the limitations and bias of the _______.

Answer 8

[human brain]

Question 9

What is required for AI applications to be effective?

Answer 9

Strong foundations, embedded in business processes, with a clear business case.

Question 10

What is the definition of artificial intelligence (AI)?

Answer 10

The ability of a digital computer to perform tasks commonly associated with intelligent beings.

Question 11

What is machine learning (ML)?

Answer 11

An AI discipline that implements computer software that can learn autonomously.

Question 12

What does a single supplier view (SSV) entail?

Answer 12

Collecting data from disparate sources to form a single, accurate record for each supplier.

Question 13

What does the Gartner Hype Cycle illustrate?

Answer 13

The evolution of technology perception through phases from innovation trigger to plateau of productivity.

Question 14

True or False: AI can solve problems without the need for good underlying data quality.

Answer 14

False

Question 15

What are two intractable problems that AI can solve for a data-driven business?

Answer 15

• Speed
• Complexity

Question 16

What is forecasting in the context of data?

Answer 16

Estimating future events based on past and present data through trend analysis.

Question 17

What distinguishes predictive modelling from forecasting?

Answer 17

Predictive modelling estimates the likelihood of specific outcomes, while forecasting gives a general judgement.

Question 18

What are the two types of AI applications used in policing?

Answer 18

• Location-based algorithms
• Predictive tools focusing on individuals

Question 19

What is the importance of a clear business case in AI implementation?

Answer 19

It aligns with the data and analytics strategy, ensuring effective AI application.

Question 20

What does the AI maturity model illustrate?

Answer 20

The journey in AI implementation from basic decision support processes to complex decision-making.

Question 21

Fill in the blank: The chief data officer becomes the focus of future _______.

Answer 21

[competitive advantage]

Question 22

What is the role of AI in decision support?

Answer 22

To improve the options and alternatives available to human decision-makers.

Question 23

What is the significance of a ‘single customer view’ (SCV) mentioned in relation to SSV?

Answer 23

It serves as a model for creating a unified view of suppliers for better data management.

Question 24

What is a major challenge for businesses using AI?

Answer 24

Navigating the balance between technology capabilities and the quality of data.

Question 25

What is anomaly detection?

Answer 25

The identification of unusual patterns that do not conform to expected behavior.

Question 26

What is the purpose of fraud detection?

Answer 26

To identify and prevent fraudulent activities within a system.

Question 27

What are examples of process automation?

Answer 27

* Automation of approvals * Automation of claims

Question 28

What role do chatbots play in business?

Answer 28

They automate customer service interactions and provide information to users.

Question 29

What is robotics in the context of business?

Answer 29

The use of automated machines to perform tasks traditionally done by humans.

Question 30

What is clustering in customer analysis?

Answer 30

Grouping customers based on shared characteristics or behaviors.

Question 31

What is sentiment analysis?

Answer 31

The use of AI to determine the emotional tone behind words.

Question 32

What is the goal of risk management?

Answer 32

To identify, assess, and prioritize risks followed by coordinated efforts to minimize, monitor, and control the probability or impact of unfortunate events.

Question 33

What technologies are used in facial recognition?

Answer 33

AI algorithms that analyze facial features and patterns.

Question 34

What is voice recognition?

Answer 34

The ability of a machine to identify and process human voice input.

Question 35

What does predictive maintenance entail?

Answer 35

Using data analysis tools and techniques to detect anomalies in equipment operation and potential defects.

Question 36

What is guided decision-making?

Answer 36

The process of using data-driven insights to inform business decisions.

Question 37

Fill in the blank: Robotic Process Automation (RPA) is a form of business process automation that uses ________ to learn and complete data processing applications.

Answer 37

[AI]

Question 38

What is the significance of data governance in fraud detection?

Answer 38

It ensures data quality and helps expose low-level fraudulent behavior.

Question 39

What percentage of frauds benefited from weaknesses in internal controls, according to a 2016 survey by KPMG?

Answer 39

61 percent

Question 40

True or False: AI in fraud detection attempts to remediate problems and provide explanations.

Answer 40

False

Question 41

What is the main function of customer service bots?

Answer 41

To assist customers by answering questions and providing information.

Question 42

What is Natural Language Processing (NLP)?

Answer 42

A field of AI that helps computers recognize the meaning of human language.

Question 43

What was the challenge addressed by the Billy Bot case study?

Answer 43

Finding good barristers’ clerks.

Question 44

What was the outcome of implementing Billy Bot?

Answer 44

A permanent increase in productivity, saving 200 hours of work a month.

Question 45

What do meaningful clusters in customer segmentation allow businesses to do?

Answer 45

Target sales and marketing efforts more effectively.

Question 46

What is a significant risk of using biased data in AI applications?

Answer 46

The AI may perpetuate or exacerbate existing biases.

Question 47

Fill in the blank: An AI application knows only about the data it is ________ to.

Answer 47

[exposed]

Question 48

What is statistical parity in measuring bias in machine learning?

Answer 48

A test to evaluate if two groups have the same probability of a positive outcome despite differing in a protected attribute.

Question 49

What is the effect of removing bias from AI algorithms?

Answer 49

It may make the algorithm less profitable.

Question 50

What is the primary task of AI applications that support complex analysis and prediction?

Answer 50

To provide insights and forecasts that the business could not easily find otherwise.

Question 51

What is one way to validate AI applications that could have been accomplished by skilled staff?

Answer 51

By conducting a human check using a sample of outputs.

Question 52

What is positive sentiment in AI applications?

Answer 52

The process of assigning positive sentiment to words and phrases in messages similar to previously identified positive messages. ## Footnote This involves using examples and human checks to validate sentiment analysis.

Question 53

What benefits do cloud-based services provide for AI applications?

Answer 53

They aggregate data from multiple sources, enabling the application to learn from a broader range of experiences and build trust through demonstrated success. ## Footnote This is particularly useful in areas like sentiment analysis and attack detection.

Question 54

What is the 'black box' problem in AI?

Answer 54

A situation where the internal workings of an AI system are not transparent, making it difficult to understand how inputs lead to outputs. ## Footnote This is especially problematic in regulated areas where decision-making transparency is required.

Question 55

What are the four 'V's of big data?

Answer 55

* Variety * Volume * Velocity * Veracity ## Footnote These components characterize the complexity and challenges of processing big data.

Question 56

Define 'big data'.

Answer 56

Data that is high volume, with lots of variety (structured and unstructured) and high velocity, making it complex and hard to process. ## Footnote This complexity can lead to challenges in data analysis and decision-making.

Question 57

What is an 'explanation by design' in AI?

Answer 57

A method where the data team documents the data fed into the AI, the assumptions made, and the logic behind outcomes to build trust in the AI's decisions. ## Footnote It helps convey the reasoning behind decisions without revealing the full decision-making process.

Question 58

What are common issues that can lead to AI disappointment?

Answer 58

* Missing data * Data leakage * Data quality issues ## Footnote These problems can hinder the AI's ability to generate valuable insights.

Question 59

True or False: AI can fully replace human decision-making.

Answer 59

False. ## Footnote Human interpretation and context are essential in decision-making, especially when AI guidance is poor.

Question 60

What two types of trust are necessary for AI to be effectively integrated into decision-making?

Answer 60

* Employees must trust AI decisions * Customers must trust AI protections and fairness ## Footnote Building this trust is crucial when using AI for recommendations or decision-making.

Question 61

How can bias in training data affect AI applications?

Answer 61

It can result in skewed outcomes that do not represent all demographics accurately, leading to unfair or unsafe decisions. ## Footnote An example is car safety features designed primarily based on male crash test dummies.

Question 62

What is an unexpected value in AI recommendations?

Answer 62

The ability of AI to provide insights or recommendations that are not obvious or standard, potentially leading to more valuable business outcomes. ## Footnote This contrasts with safe but uncreative recommendations that may not engage users.

Question 63

What should be considered when aligning AI with data and analytics strategy?

Answer 63

* Real-time data needs * Impact on customer relationships ## Footnote These considerations help ensure that AI is used effectively and adds competitive advantage.

Question 64

What characterizes a data-driven model?

Answer 64

Ensuring that everyone in the organization has the best data in the right format when making decisions. ## Footnote However, this does not address issues like information overload or bias.

Question 65

What is essential for AI to transition from a simple tool to a creative catalyst?

Answer 65

AI must be allowed to innovate processes for the business, potentially with little human involvement. ## Footnote This requires careful management of expectations and capabilities.

Question 66

What is the main takeaway regarding AI and data quality?

Answer 66

AI cannot compensate for poor data engineering and requires careful introduction and management. ## Footnote Utilizing external cloud-based applications can enhance learning about AI capabilities.