This chapter introduces the volume as a whole, outlining the current and
future directions in the legal use of data, and exploring how data can be utilized in the
legal system to promote justice and human rights, as well as enhance the legal
decision-making process itself.
Part I examines some of the ways in which Artificial Intelligence (AI) and Machine
Learning (ML) technologies are marshalling data to improve legal decision-making.
The included chapters examine the ways in which data science has been used to
improve legal decision-making, from its inception in the mid-twentieth century to
Groningen’s school's more recent work on using AI to model the fact-finding process
itself. Data, when governed judiciously, can be used to improve legal decision-making
and thus improve access to justice, better justify decisions, reduce biases in decisionmaking, and evaluate evidence to improve accuracy and reduce miscarriages of justice.
Part II examines new strategies to govern the use of data in the legal system:
identifying and addressing cognitive biases among forensic scientists, regulating the
forensic use of bioinformatics in the criminal justice system, and eliminating the use of
false legal information hallucinated by AI systems.
Part III of this book describes some novel forensic applications of genetic data,
particularly in the field of bioinformatics and its advances in human identification.
Some of the most significant advances have been made in the field of bioinformatics
and its application to human identification. The chapters in this section focus on these
developments, examining how advances in SNP sequencing, combined with
computational methods for kinship identification, are leading to the clearance of
previously unsolvable cases.
Keywords: Artificial Intelligence, AI and law, Argumentation theory, Bioinformatics, Data science, Ethics of AI, Forensic genetics, Forensic genomics, Forensic science, Genetic genealogy, Human identification, Kinship, Legal ethics, Machine learning, Philosophy of evidence.
