Policy-Making and Data Economy at the city level: utopia or reality?
13:30-16:30 January 27

½ day
Beginner level

Details

Despite the Data and the AI hype, a number of grey zones of exploitation and several open challenges still represent concrete obstacles in the value creation, above all in the private-public collaboration and the effective arise of a "Data Economy and Data Market” at the city level.


For instance:

  • Finding valuable data is still the main problem despite the impressive amount of digital information we produce every day and the Open Data movement.
  • Hiring professionals is hard, as well as team assembling. Furthermore, we observe a lack of people able to “translate and communicate” the data insights.
  • The gigantic ethic-of-data theme is only superficially explored.
  • Regulated systems failed to keep the pace of technology improvements (despite on the GDPR arrival).
  • The evaluation of models did not reach a universal benchmark yet. What is the best way to measure the goodness of a specific solution?
  • Bias are affecting Machine Learning and Deep Learning implementations.
  • Transition from “grid” (deterministic, functional, efficient, … ) to complex is hard, particularly for companies, organizations, and governments that have a strong legacy in infrastructures and processes.

Generally speaking: today data, ML, DL are effectively used in industrial and for-profit business cases while the data-driven evidence-based policy-making is far from reaching the initial promises.


Throughout the application of our conceptual framework canvas (namely the Data Ring - dataring.eu) we will explore different end-to-end scenarios in terms of:

  • Enabling factors
  • Best practices
  • Technical aspects
  • Threats

Agenda

  • Workshop introduction (Who we are, Why we are here)
  • Our perspective on Machine Learning and AI open challenges, particularly in the field of Policy Making at the city level.
  • Interactive discussion aimed to collect ideas and common problems.
  • Data Ring Canvas explanation
  • Interactive session: attendants will be divided in groups and guided to fill the canvas using given use-cases
  • Group will presents the output of their work
  • Conclusions and Wrap-up

The main goal of the workshop is to brainstorm, analyze and define collaborative scenarios where local governments, companies and community of Data Scientists might collaborate to solve citizenship problems.


Outcome

After a theoretical assessment where common language and notions will be shared, the participants will take part in a group activity aimed at “drawing" end-to-end scenarios where local governments, companies and community of Data Scientists might collaborate to generate social and economic value.


As a secondary output the participants (tech, executives and business people) will have a complete overview, and eventually more comprehensive perspectives, on data projects and will be trained to use the Data Ring tool to effetely address future data-driven projects.


Prerequisites

The ideal group of participants we'll have both a technical background or experience in policy-making and connection with public administration to collect different perspective of the scenario we'll tackle together.

Organizers

Stefania Delprete

Data scientist, TOP-IX

Twitter

Christian Racca

Design Engineer, TOP-IX

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