Artificial Intelligence in the Courtroom: Friend or Foe?

Correctional Offender Management Profiling for Alternative Sanctions is the US’s primary predictive analytics tool in the courts. When artificial intelligence (AI) is deployed in high-impact human environments like courtrooms, a volcano of ethical dilemmas erupts. AI improves consistency and efficiency and reduces human error. However, it lacks transparency and moral judgment. Furthermore, AI is a vessel for bias that slips into algorithms, damaging human lives. AI’s consequences generally fall into two categories: broad human rights violations—affecting privacy, education, life, and due process—and systemic bias, exemplified by the unfairness of tools like the COMPAS sentencing algorithm. There is also a clear unequal treatment and violation of the defendant’s liberty. Nevertheless, with transparency of algorithms, there is a brighter path forward. To ensure the safe, widespread use of artificial justice, interdisciplinary collaboration is required. 

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Ethics Behind Industry-Funded Research

Many researchers who fail to obtain public funding turn to private companies for sponsorship, giving rise to “industry-sponsored research.” In comparison to publicly funded research, industry-sponsored research often displays more bias. More often than not, findings support sales promotions or generate revenue for sponsor companies. This bias raises questions regarding the ethics of industry-funded research. However, acknowledging the difficulty in obtaining public funding may help mitigate the harmful effects of industry-funded research. Several methods to mitigate the bias prevalent within industry-funded research may guarantee the legitimacy of sponsored reports.

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The Role of Bias in Scientific Research

The world is buzzing once again with supposed evidence of alien life. While under oath, Jaime Mausson presented two bodies he claims are of extraterrestrial origin to the Mexican Congress. However, experts are skeptical of his findings, claiming they have no real scientific basis. This case brings to question the role of bias in scientific research and how the resulting spread of misinformation can cross the line into becoming harmful.

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