Iliff Artificial Intelligence
Building a sustainable future for humans and machines
A trust approach to AI sets as its goal transforming the culture of an organization, from data scientists to marketing to accounting. Trust takes a whole lifecycle approach to develop dispositions and practices toward cultivating trust at every stage of the AI development process, from problem definition to deployment and maintenance. Rather than proxying responsible design to an ethics board, a trust approach to AI involves the whole community in the task of developing an ecosystem of trust.
The ai.iliff learning partner aims to make humanities education more widely available, more efficient, more diversified, and more individualized than humanities education has been to date. The learning partner dynamically engages students by constantly evaluating what concepts have been learned and nudging students toward concepts and perspectives that have not been raised in the discussion. The learning partner will eventually be made available in learning management systems such as Canvas.
Bias in artificial intelligence is connected to bias in humans. How can our partnership with machines make us more aware of the bias operative in society and help us to select biases that reflect our desired future rather than replicate our behavior in the past? We are developing a set of practices that will make bias more visible in all stages of the AI development lifecycle so that we can make values based decisions in adjusting and managing this bias.
Much of the hype and fear around the emergence of AI in so many areas of society can be addressed through education. We design and deliver custom learning opportunities in areas related to AI and Society, Data Citizenship, and Human-AI interface. We can provide online, hybrid, or on site learning opportunities.