Challenge 5
Artificial Intelligence: Predict SDG indicators from publicly available data
Challenge title and general facts
The big idea: use country data over the years to identify
what factors influence a SDG
Challenge type: Mini (4 weeks)
Challenge owner: Universidade Aberta
Facilitator: José Coelho, Vitor Rocio
Facilitator Contact data: jose.coelho@uab.pt,
Challenge is related to the topic of Artificial Intelligence.
Context & relevance: in general relating to SDG / specific to a field of vocational application
This challenge is completely related to SDG, but not specific to a field of application. Students may choose a SDG according to their preference or labour context, studying their depending factors and producing recommendations for countries and companies. The focus is on ML techniques applied to past data.
Variants of the challenge
N/A - each student can select a SDG and target indicator, so the challenges may be very different, but solved with similar techniques
Business partner in an industry or a research field
N/A
Prerequisites of the learners
Functional requirements
Software: R language
Hardware: N/A
Working Space: The R Project for Statistical Computing
Impact
Production of sets of recommendations for public bodies/companies in order to improve the identified SDG, based on ML findings.
Open Issues and questions
Indicators that the ML techniques do not prove to influence the SDG may be reported as irrelevant, but it is not clear how that can be reflected on the recommendations.
