FPSY3900: The Future of Jury Decision-Making

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Lecture 10 (Final Testable Lecture)

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Culture Differences in Jury Deliberations & Jury Decision Making between South Korea and the United States (Alcohol)

  • identify differences between collectivist and individualistic jurors

  • communication styles

  • how groups’ deliberations differed

  • attribution styles; relates to the defendant’s behaviour

    • blame → is attributed to something internal or external

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Lee et al. (2025) → Method

  • 28 mock jury deliberations (14 Korea/14 US)

  • Analysis of transcripts

What are the findings?

  • Less conformity (less likely to conform to the group)

  • Incorporation of multiple arguments

    • tend to look at more arguments/components to find their final verdict

  • Acknowledgment of mitigating factors (external attribution)

    • alcohol abuse

    • more likely to attribute blame to external forces

  • No differences in final sentencing 

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House of Worship Mass Shooting: The Influence of Defendant Age, Religion and Victim Religion on Mock-Juror Decision-Making (Article)

looked at Christian vs. Muslim defendants, victims

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Vettese et al. (2024) → Method

  • 321 participants

    • all-white Canadians

  • Mock trial transcripts regarding mass shooting at a place of worship

  • asked to provided final verdicts

What are the findings?

  • Christian defendants = more guilty than Muslim defendants

    • seen less favourably

    • for christians they are seen as more guilty

  • Muslim victim = higher guilt ratings

    • more favourably when the defendant is christian

  • mock jurors assigned higher guilt in victims

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<p><strong>Delayed Reporting &amp; Jury Decision-Making</strong></p>

Delayed Reporting & Jury Decision-Making

  • don’t know how to report

  • may not have an accurate depiction of the events

  • feel embarrassed

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How Length of & Reason for Delayed Reporting Influence Mock-Jurors’ in a Sexual Assault Trial (Article)

  • delaying cases

  • fear of retaliation

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Thompson & Pozzulo (2024) → Method

  • 709 Mock jurors

    • how truthful they thought the testimonies were from both sides

  • Delayed reporting and reason for delay

What were the findings?

  • Less delay = increase guilty verdict

  • Delay reporting due to family concerns = increase guilty verdict

  • dichotomos verdict

  • men SA/rape the women

  • shorter the delay it looked better for the victim

  • mock jurors were more likely to render a guilty verdict

  • guilty verdict if the victim delayed due to scared for family finding out

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Martin & Monds (2023) → Method

  • 228 mock jurors

  • Rape/robbery transcript

    • committed against a women when they were under the influence

What were the findings?

  • Alcohol seen as detrimental to victim credibility

    • do you actually recall the events that occurred

    • intoxication status failed to influence verdict decisions

  • No difference in verdict decisions

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Threat of pre-trial publicity can threaten blank responses

open-minded

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Interventions for the threat of pre-trial publicity

  • less biased reporting

  • expert testimony

    • to understand the impact of technology

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The temptation to seek information

  • motivation to be accurate

  • case-specific searches

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Intervention for the temptation to seek information

restricting access

  • when told not to look at the media but they still continue to do so

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Asian countries have a more blank notion

interdepent

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7 Guidelines for AI Use in the Court

  1. Protect judicial independence

  2. Use AI consistently with core values and ethical rules

  3. Have regard to the legal aspects of AI use

  4. AI tools must be subject to security standards

  5. AI tools must provide understandable explanations for decision-making

  6. Courts must track AI impact

  7. Program of education and user support

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Guideline 1 – Protect judicial independence

  • AI use should not be governed by a state agency

  • Constitutionally independent courts retain judicial independence

    • government should not be intervening in the ai court systems

    • could play a big part in the courts an d must firmly uhold the idea of independence

    • should not ben e governend by AI structure

  • AI applications harbour the potential to erode judicial agency and independence.

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Guideline 2 – Use AI consistently with core values and ethical rules

  • AI use should align with core values and judicial ethics

  • These include independence, integrity and respect; diligence and competence; equality and impartiality, fairness, transparency, accessibility, timeliness and certainty

  • AI can remove core ethical values, so we should not let it occur

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Guideline 3 – Have regard to the legal aspects of AI use

  • Courts should be aware of the source material used to train AI systems

  • Consideration for the legality of generative AI practices

  • sensitive data are being sent to the courts; giving AI this information

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Guideline 4 – AI tools must be subject to security standards 

  • AI tools bring unique security challenges

  • Robust information and cybersecurity program

  • Target security of information and tampering

  • unauthorized data

  • data is vulanerbale, we need to protect AI components from tamepring

  • ensuring data protection

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Guideline 5 – AI tools must provide understandable explanations for decision-making 

  • AI can be used to improve court efficiency

  • Must ensure the explainability of AI systems

  • provide lcear outputs

  • should be easy for us to interpret to test outputs in courts

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Guideline 6 – Courts must track AI impact 

  • Administrators must perform a comprehensive, formal, and impartial assessment of its impact

  • This relates to judicial independence, workload, backlog reduction, privacy, security, access to justice, and the court’s reputation

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Guideline 7 – Program of education and user support  

  • Judiciary must have appropriate knowledge of AI systems

  • AI should not be employed without users undergoing a comprehensive educational process

  • should not be tampered with

  • judges/court personnel must be trained to work alongside AI

  • to help make sure the courts are running smoothly

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AI in the Courtroom: In class video

robot is acting as a judge

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What was the traditional jury shortfalls?

  • backlog of cases

    • takes way too long; years

  • consistency of verdicts and hung juries

    • juries can be divided in verdicts

  • Unreasoned verdicts and witness evaluation 

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How would AI help the backlog of cases?

  • Decisions 7x faster

  • 24h juries

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How would AI help the consistency of verdicts and hung juries?

  • Reliance on code and algorithm (not values and beliefs)

  • Objective and consistent

    • no personal biases

    • remove voire dire process

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How would AI help the unreasoned verdicts and witness evaluation?

  • Detection of behaviour/reliability 

  • Consistent observation of ‘live evidence’

  • program AI to do reasonings

  • no issues in interpreting legal proceedings

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Potential limitations/risks of AI

  • Jury tampering

  • Bias

  • Lack of conscience 

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Victim Intoxication & Jury Decision Making

  • Impact on Perceived Credibility

  • Role in Causation & Blame Attribution

  • Influence on Legal Standards

  • Scientific vs. Lay Interpretation

  • Case-Specific Context

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Examples of Traditional Jury Limitation

  • bias

  • backlog of cases

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Benefits of an AI Jury

  • going through cases faster

  • consistency of verdicts and hung juries

  • unreasonsed verdicts and witness evalutation

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T/F: Unlike human juries, proponents of AI juries argue that an AI jury would be less susceptible to the misinterpretation of the law

True

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Jury Tampering

  • Vulnerable to hackers

    • no matter what security measures

  • Possible to tamper with trial outcomes

  • easily sway

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Bias in AI

  • Algorithmic bias

  • Error in AI training

  • Human bias built into AI

    • hold biases given from the humans who created it

    • may embed their own personal biases into the code/algorithm

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Lack of conscience in AI

  • AI lacks moral judgement

    • who is keep in line of morals/ethics

  • Cannot identify moral issues

  • No ‘code’ for ethics