I watched the three videos you shared and found them to be very informative. They helped me to understand the different types of bias and how they can manifest in our professional lives.

In my field of study, which is artificial intelligence, there is a gender bias. Men are more likely to be hired for AI jobs, and they are also more likely to be promoted to leadership positions. This is likely due to the fact that the field of AI is still relatively new, and there are fewer women who have the skills and experience necessary for these positions.

There is also a racial bias in the field of AI. Black and Hispanic people are less likely to be hired for AI jobs, and they are also more likely to be passed over for promotions. This is likely due to the fact that these groups are often underrepresented in STEM fields, and they may not have the same access to resources as white people.

In addition to gender and racial bias, there is also ageism, ableism, and homophobia in the field of AI. Older people, people with disabilities, and gay and lesbian people are less likely to be hired for AI jobs, and they are also more likely to be passed over for promotions. This is likely due to the fact that these groups are often seen as being less capable or less qualified than their straight, white, male counterparts.

There are a number of things that we can do to consciously recognize and reject bias in our profession. First, we need to be aware of our own biases. We can do this by taking implicit bias tests and by reading about the different types of bias. Once we are aware of our biases, we can start to challenge them. We can do this by actively seeking out information and experiences that challenge our preconceived notions. We can also talk to people from different backgrounds and experiences to learn more about their perspectives.

In addition to challenging our own biases, we can also work to create a more inclusive environment in our field. We can do this by hiring and promoting people from diverse backgrounds. We can also create policies and procedures that are fair and equitable for everyone.

By taking these steps, we can help to create a more just and equitable field of artificial intelligence.

Here are some additional thoughts on how to recognize and reject bias in our profession:

• Be mindful of our language. The words we use can perpetuate bias, even if we don’t intend them to. For example, using terms like “manpower” or “fireman” can exclude women from these roles.
• Be aware of our assumptions. We all make assumptions about people based on their appearance, gender, race, age, and other factors. These assumptions can lead to bias in our decision-making.
• Be open to feedback. If someone tells us that we have said or done something that is biased, we should listen to them and take their feedback seriously.

Be willing to learn. There is always more to learn about bias. We should be open to reading books, articles, and blog posts about bias, and we should attend workshops and trainings on the topic.