Τεχνητή νοημοσύνη και δικαιοσύνη / Δικαστικό σύστημα
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Τεχνητή νοημοσύνη ; Δικαιοσύνη ; Δικαστικό σύστημαAbstract
The use of artificial intelligence, algorithmic decision-making systems and machine learning has become common practice across a wide range of sectors. Computer-raised data are said to be the “oil” of the 21st century as their use and cross-referencing are producing a whole new wealth. AI is now used in a wide and ever-growing range of situations. We use algorithmic systems for spam filtering, traffic planning, logistics management, diagnosing diseases, speech recognition etc. The justice system is not immune to this trend. Predictive algorithms are rapidly spreading throughout the justice system. They are currently used in civil justice for calculating scales of compensation and online dispute resolution and in criminal justice system to more efficiently allocate police resources, identify potentially dangerous individuals at specific locations (predictive policing) and advise judges about pretrial detention, bail hearings and sentencing. Moreover, lawyers see the possibility of using ΑΙ systems to provide their clients with better informed advice by assessing the chances of a procedure’s success. Although algorithmic decision-making can seem rational, neutral, and unbiased and justice systems may have significant benefits from it, it can also lead to unfair and illegal discrimination and threaten human rights, such as the right to liberty (article 5 ECHR), the right to a fair trial (article 6 ECHR), the right to privacy (article 8 ECHR and GDPR) and the prohibition of discrimination (article 14 ECHR). Studies have demonstrated that algorithms can unintentionally lead to the replication of human biases. The risk of discrimination arising when important decisions are made based on data such as gender, age and perhaps race is an extremely important concern for civil society. It is imperative that the use of algorithmic systems in justice is properly scrutinized within a legal framework. The effective implementation of ethical principles in relation to AI systems requires an ‘ethics by design’ approach. Legal regulation of predictive algorithms should be based on universally accepted ethical principles, such as: transparency, (including accessibility and explicability), non-discrimination (including liability and the availability of remedies), safety and security of the systems and privacy and data protection.
Postgraduate Studies Programme
Δίκαιο και Τεχνολογίες Πληροφορικής και Επικοινωνιών (MSc in Law and Information and Communication Technologies)Department
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών ΣυστημάτωνNumber of pages
57Language
GreekCollections
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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα