Readings Week 1

Question 1

Ground truth in AI training:

Answer 1

labels assigned to the data to train a ML model to link inputs and outputs.

Question 2

Lebovitz et al (2021) - “Is AI ground truth really “true”? The dangers of training and evaluation AI tools based on experts’ know-what.”:

What is the additional risk of relying too much on AI?

Answer 2

Human data → used to teach AI → AI gets very reliable → only AI is used → only AI based data output → AI data used to teach AI → might inhibit learning and process improvement)

Question 3

What is a smart object?

Answer 3

Objects that are able to collect, process and communicate data concerning its functionality and operating environment

Question 4

Furtak et al (2015) Designing Information Systems with Predictive Analytics (DISPA) (4 steps)

Answer 4

1. Goal definition
2. Develop / build
3. Justify / evaluate
4. Process evaluation and conclusions

Question 5

What is a knowledge graph according to Chaudhri et al (2021)?

Answer 5

“A knowledge graph is a directed labeled graph in which we have associated domain specific meanings with nodes and edges.

Anything can act as a node, for example, people, company, computer, etc. An edge label captures the relationship of interest between the nodes, for example, a friendship relationship between two people, a customer relationship between a company and person, or a network connection between two computers, etc.”

Question 6

Why use KGs for data integration (3)? Chaudhri et al (2021)

Answer 6

1. Reduces the costs of starting with a data integration project
2. Easy to adapt
3. Very suited for answering questions that require examining relationships across the graph

Question 7

Characteristics of modern KGs (3)? Chaudhri et al (2021)

Answer 7

1. Bigger scale
2. Bottom up design approach
3. More automation

Question 8

Front end technologies: (4) Frank et al (2019)

Answer 8

1. Smart manufacturing
2. Smart products
3. Smart supply chain
4. Smart working

Question 9

Base technologies (4): Frank et al (2019)

Answer 9

1. Internet of things
2. Cloud services
3. Big Data
4. Analytics