How Humans and AI Systems Can Work in Tandem to Mitigate Bias?
According to a data released by IBM, there are over 180 different human biases that have been classified and defined by experts. The report further states that any of these biases can affect the manner in which we take our decisions. This is exactly where AI based systems can come to our rescue. Students studying psychology should understand this concept more as this is going to be one of the most promising future careers in psychology that they can opt for.
In fact, Artificial Intelligence with the theory of common sense/mind has the immense potential of benefiting our society in multiple ways. However, the biggest question is how an increase in realism, particularly in the mimicking of human form will result in increased acceptance and trust for AI devices among users. Alternatively, many also argue whether AI devices have the ability to tackle biases or not. Continue reading to discover how humans as well as AI systems can work in tandem to mitigate biases.
Developing AI Machines to Tackle Bias
The capabilities of AI machines are much dependent on the data you feed in them. As a matter of fact, bad data could contain gender, racial and even ideological biases. However, many AI-based machines will be trained with bad data, thus making it an ongoing issue. But, technology experts believe that biases can be easily tamed and in fact AI machines that are capable of tackling human biases will attain maximum success.
It must be noted that both machines and humans, in essence, look to avoid biases and thus prevent any kind of discrimination. In fact, as AI is being increasingly adopted, the problem of reducing bias in the AI systems is also being escalated. Bias in Artificial Intelligence based systems occur within the algorithmic or data model. Thus, as organizations come together to create AI systems that can be trusted, it's important to develop as well as train these machines using data that isn't biased. In fact, the need of the hour is to create algorithms that are easy to explain.
Mitigating Bias
It is crucial to constantly identify as well as mitigate bias in order to build trust and to ensure that these technologies will impact the society positively. In fact, researchers in organizations like IBM are focusing their efforts on developing automated algorithms that are capable of detecting biases. These algorithms are being adequately trained and created to mimic the anti-bias process in humans to facilitate decision making as well as for mitigating the inbuilt biases.
This also includes evaluating how consistently we (or AI systems) take decisions. In case there exists any difference within the solution selected for two distinct problems, even though fundamentally each situation is similar, then in such a case there can be bias against or a couple of non-fundamental variables. In terms of how human operate, this can emerge as xenophobia, racism, ageism or sexism.
Conclusion
To sum up AI practitioners and business leaders need to determine how AI can assist them to correct biases. They need to develop processes as well as practices for testing for and mitigating bias within AI machines. This can happen through conversations about the biases in human decision-making as well as by fully exploring how machines and humans can work together to mitigate biases.
To learn more about psychology of AI, check out - https://acadru.com/learning-modules/view/interpreting-machine-psychology. Acadru is a multi-disciplinary learning platform for senior school and college students to learn about unique topics, get project ideas, build skills, and learn about jobs and careers of the future.
In fact, Artificial Intelligence with the theory of common sense/mind has the immense potential of benefiting our society in multiple ways. However, the biggest question is how an increase in realism, particularly in the mimicking of human form will result in increased acceptance and trust for AI devices among users. Alternatively, many also argue whether AI devices have the ability to tackle biases or not. Continue reading to discover how humans as well as AI systems can work in tandem to mitigate biases.
Developing AI Machines to Tackle Bias
The capabilities of AI machines are much dependent on the data you feed in them. As a matter of fact, bad data could contain gender, racial and even ideological biases. However, many AI-based machines will be trained with bad data, thus making it an ongoing issue. But, technology experts believe that biases can be easily tamed and in fact AI machines that are capable of tackling human biases will attain maximum success.
It must be noted that both machines and humans, in essence, look to avoid biases and thus prevent any kind of discrimination. In fact, as AI is being increasingly adopted, the problem of reducing bias in the AI systems is also being escalated. Bias in Artificial Intelligence based systems occur within the algorithmic or data model. Thus, as organizations come together to create AI systems that can be trusted, it's important to develop as well as train these machines using data that isn't biased. In fact, the need of the hour is to create algorithms that are easy to explain.
Mitigating Bias
It is crucial to constantly identify as well as mitigate bias in order to build trust and to ensure that these technologies will impact the society positively. In fact, researchers in organizations like IBM are focusing their efforts on developing automated algorithms that are capable of detecting biases. These algorithms are being adequately trained and created to mimic the anti-bias process in humans to facilitate decision making as well as for mitigating the inbuilt biases.
This also includes evaluating how consistently we (or AI systems) take decisions. In case there exists any difference within the solution selected for two distinct problems, even though fundamentally each situation is similar, then in such a case there can be bias against or a couple of non-fundamental variables. In terms of how human operate, this can emerge as xenophobia, racism, ageism or sexism.
Conclusion
To sum up AI practitioners and business leaders need to determine how AI can assist them to correct biases. They need to develop processes as well as practices for testing for and mitigating bias within AI machines. This can happen through conversations about the biases in human decision-making as well as by fully exploring how machines and humans can work together to mitigate biases.
To learn more about psychology of AI, check out - https://acadru.com/learning-modules/view/interpreting-machine-psychology. Acadru is a multi-disciplinary learning platform for senior school and college students to learn about unique topics, get project ideas, build skills, and learn about jobs and careers of the future.
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