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AUTOMATING INJUSTICE: THE USE OF ARTIFICIAL INTELLIGENCE & AUTOMATED DECISIONMAKING SYSTEMS IN CRIMINAL JUSTICE IN EUROPEABOUT FAIR TRIALS Fair Trials is an international human rights NGO that campaigns for fair and equal criminal justice systems. Fair Trials team of experts expose threats to justice and identify practical changes to fix them. The organisation produces original research, campaigns to change laws, supports strategic litigation, reforms policy and develops international...
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01
Start by assessing the current processes that contribute to injustice.
02
Identify the specific injustices you want to address.
03
Gather data and information related to the injustices.
04
Choose automation tools that can help streamline processes and eliminate bias.
05
Develop a plan for integrating automation into the existing systems.
06
Test the automated systems to ensure they effectively address the identified injustices.
07
Continuously monitor and adjust the automation processes to improve outcomes.

Who needs automating injustice?

01
Organizations focused on social justice and equality.
02
Government agencies that aim to reduce bias and promote fairness.
03
Non-profit groups working to assist marginalized communities.
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Businesses looking to improve their hiring and evaluation processes.
05
Educational institutions aiming to create more equitable environments.
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Automating injustice refers to the use of automated systems and algorithms that perpetuate or exacerbate existing biases and unfair practices in decision-making processes.
Individuals or organizations that detect or suspect instances of automated systems leading to unjust outcomes may be required to file a report of automating injustice.
To fill out a report of automating injustice, provide accurate information about the incident, including the nature of the injustice, the parties involved, and the outcomes, as well as any supporting documentation.
The purpose of automating injustice reporting is to identify and rectify unfair practices in automated systems to promote fairness, accountability, and transparency in decision-making processes.
Information that must be reported includes details of the automated system in question, the specific unjust outcomes observed, any relevant data or evidence, and the impact on affected individuals or groups.
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