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Machine Learning Bias Algorithms in the Courtroom

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It is well known that computers can learn from the data and process it faster than humans. But with that power comes a new set of issues in the courtroom: machine learning models that can learn to anticipate or infer the behaviors of jurors in the court. With a few examples, I will show that these models could be biased and produce unintentional results that can make or break a case. As an attorney, I worked in trial rooms every day. The first thing I noticed about jury selection is the constant media hype, which can make some jur

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Machine learning technology, often referred to as artificial intelligence (AI) or data science, has significantly impacted various fields and has helped make our lives easier. It is undeniable that machines have the potential to replace human beings in the workplace. view However, there is one issue that is still left untouched: the role of human decision-making, including its flaws. Machine learning algorithms can lead to imbalanced results and injustice. In the United States, for example, the field of criminal justice has been experiencing such problems. The country’s court systems

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In recent times, machine learning has revolutionized the practice of law by helping the courts make informed decisions. The advent of machine learning algorithms has enabled the courts to analyze vast amounts of data, making a legal judgment more precise and faster. This has transformed the legal system, enabling the courts to make more accurate decisions based on relevant information and statistics. However, there is a significant concern about the unintended consequences of these machine learning algorithms. Many cases that were previously resolved through trial court decisions have now been decided through machine learning algorithms. It can lead to the im

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Machine Learning Algorithms are powering a new wave of disruptive technologies. As such, they have been put to use in the courtroom and are being used to analyze and interpret complex data, which in turn has transformed the practice of law and justice. Machine Learning is transforming how legal practitioners approach cases. Machine Learning algorithms work by analysing vast amounts of unstructured data generated by electronic devices such as mobile phones, wearables, traffic sensors, and sensors in vehicles, as well as in personal interactions like social media, text, and

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In recent years, there has been a significant rise in the popularity of Artificial Intelligence (AI) in the legal industry. Machine Learning (ML) algorithms, for example, have found applications in legal cases. In the past, these algorithms were limited to the field of cybersecurity, but now they are being used to analyze legal documents, analyze patterns and trends in court cases, and even predict crime rates. Unfortunately, these ML algorithms may be biased. The problem is that they are trained on a dataset that often has a tendency to exclude certain

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Machine Learning Algorithms have been in the news lately, in particular with regards to their application in the courtroom. These algorithms, while generally useful, can be susceptible to biases that could affect their performance in criminal cases. my explanation One study found that a common machine learning algorithm, Random Forest, could result in miscarriages of justice in drug trials. While these results were anecdotal, it does provide some insight into the potential for algorithmic errors in high-stakes cases. Another study analyzed the results of machine learning algorithms in the courtroom and found

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