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ETHICS AND CONTROL OF ARTIFICIAL INTELLIGENCE

1-4 DAYS DUAL MODE
May 13-14-19-20, 2026
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Early - bird
-100.00 euro
With enrollment by
13.04.2026
Registration deadline: 02.05.2026

In a world increasingly permeated by artificial intelligence, ethical reflection and responsible control of technologies have become essential issues. This course explores the moral dilemmas, regulatory challenges, and governance tools necessary for the responsible use of AI.

Real cases, regulatory principles, and scenarios will be analyzed to understand how to steer the innovation introduced by AI toward fair, transparent, and secure use.

 

The registration fee includes access to confidential asynchronous content through the Smart Academy platform.

Date
May 13-14-19-20, 2026
Industry
BANKING, INSURANCE, CROSS INDUSTRY
Subject areas
Digital Innovation & FinTech
Language
Italian
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Registration fee
Adherent Cetif
€1500.00 + VAT *
Non-Adherent Cetif
1700.00 + VAT*
*Quota per participant
Discounts and economic benefits
To whom it is addressed
  • Professionals from any industry, from various corporate functions, with particular reference to the areas of Digital, Compliance, Risk Management, Audit, Legal, and IT.
  • Those who are involved in implementing AI projects and wish to enhance their skills.
Formative Objectives.

Enable participants to grasp the key concepts and differences between human reasoning and algorithmic reasoning, and learn about AI verification and monitoring techniques.

The format

Innovative and effective teaching techniques geared toward the transfer of knowledge and behavior through:

  • theoretical lectures

  • moments of consolidation and critical revision of content

  • Exercises and simulations

  • use case and benchmark

The Course will be held in. Dual Mode: the participant at the time of registration will be able to communicate the most convenient mode of fruition.

Course Schedule.

  • AI ethics: old problems and new problems
  • Bias, Opacity, and Epistemic Delegation: The Challenges of AI
  • Risk and rationality in AI

 

  • Algorithmic bias and human bias: why (and how) AI can discriminate
  • Types of algorithms and the risks of discrimination
  • Supervised and unsupervised algorithms
  • Algorithms and artificial intelligence (how machines learn with algorithms)
  • Algorithmic optimization in machine learning and the development of discriminatory behaviors and biases
  • The precursors: Isaac Asimov's laws of robotics
  • The regulatory principles of the AI Act
  • The concept of algorithmic fairness and particularities
  • Controlling an AI: the measures of fairness (statistical parity, accuracy parity, ...)
  • Examples of application
Download the program

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