Kerry Bodine

I love that you just said that the tool, the consequence scanning tool can be used really quickly. We could talk about something and do it in five minutes. You could take a couple of weeks to do it, but that's nothing in terms of, you know, how long it's going to cost to develop, you know, a big AI product service feature, whatever it is.

I love that you just said that the tool, the consequence scanning tool can be used really quickly. We could talk about something and do it in five minutes. You could take a couple of weeks to do it, but that's nothing in terms of, you know, how long it's going to cost to develop, you know, a big AI product service feature, whatever it is.

I love that you just said that the tool, the consequence scanning tool can be used really quickly. We could talk about something and do it in five minutes. You could take a couple of weeks to do it, but that's nothing in terms of, you know, how long it's going to cost to develop, you know, a big AI product service feature, whatever it is.

And so take the time to do that, get out in front of some of those decisions beforehand. And then the other part of your question is we all need to get better at just understanding the types of potential harms. So there is psychological harms, there's financial harms, environmental harms. I mean, there's a whole list of the different types of harms, the severity of the harms.

And so take the time to do that, get out in front of some of those decisions beforehand. And then the other part of your question is we all need to get better at just understanding the types of potential harms. So there is psychological harms, there's financial harms, environmental harms. I mean, there's a whole list of the different types of harms, the severity of the harms.

And so take the time to do that, get out in front of some of those decisions beforehand. And then the other part of your question is we all need to get better at just understanding the types of potential harms. So there is psychological harms, there's financial harms, environmental harms. I mean, there's a whole list of the different types of harms, the severity of the harms.

This is a minor harm or really severe harm. And then there's a duration of the harm as well, from acute to intergenerational. If you build an AI that denies a certain portion of the population home loans, that has intergenerational impacts, which gets us back to our long-term thinking. And so there's just many aspects of how we need to really start thinking about the decisions that we're making.

This is a minor harm or really severe harm. And then there's a duration of the harm as well, from acute to intergenerational. If you build an AI that denies a certain portion of the population home loans, that has intergenerational impacts, which gets us back to our long-term thinking. And so there's just many aspects of how we need to really start thinking about the decisions that we're making.

This is a minor harm or really severe harm. And then there's a duration of the harm as well, from acute to intergenerational. If you build an AI that denies a certain portion of the population home loans, that has intergenerational impacts, which gets us back to our long-term thinking. And so there's just many aspects of how we need to really start thinking about the decisions that we're making.

And we need to start thinking about it now.

And we need to start thinking about it now.

And we need to start thinking about it now.

And AI is even more unpredictable than humans. Exactly. And one of the things that I'm seeing in my classes and in my consulting is that a lot of leaders don't even really understand that there's... When you talk about training, there's the data and there's the model. And there are... different ways that you can train your AI employee by changing different parts of that equation.

And AI is even more unpredictable than humans. Exactly. And one of the things that I'm seeing in my classes and in my consulting is that a lot of leaders don't even really understand that there's... When you talk about training, there's the data and there's the model. And there are... different ways that you can train your AI employee by changing different parts of that equation.

And AI is even more unpredictable than humans. Exactly. And one of the things that I'm seeing in my classes and in my consulting is that a lot of leaders don't even really understand that there's... When you talk about training, there's the data and there's the model. And there are... different ways that you can train your AI employee by changing different parts of that equation.

And data, oh my gosh. I mean, again, this could be an entire episode, but I'm doing research right now on the AI readiness of organizations in terms of their data. And, you know, if you if you talk to anyone, there's data issues in any one system. And then you need to start connecting those systems and making sure that the data is consistent across all. Oh, my gosh.

And data, oh my gosh. I mean, again, this could be an entire episode, but I'm doing research right now on the AI readiness of organizations in terms of their data. And, you know, if you if you talk to anyone, there's data issues in any one system. And then you need to start connecting those systems and making sure that the data is consistent across all. Oh, my gosh.

And data, oh my gosh. I mean, again, this could be an entire episode, but I'm doing research right now on the AI readiness of organizations in terms of their data. And, you know, if you if you talk to anyone, there's data issues in any one system. And then you need to start connecting those systems and making sure that the data is consistent across all. Oh, my gosh.

Data is going to be one of the biggest areas that organizations need to focus on. And I don't think most organizations are understanding data. just how big the data lift is going to be in order for them to create all of these magical AI systems that they are envisioning.

Data is going to be one of the biggest areas that organizations need to focus on. And I don't think most organizations are understanding data. just how big the data lift is going to be in order for them to create all of these magical AI systems that they are envisioning.