Demand for Transparency in AI Grows as Howso Tackles Black Box AI
In today’s AI-driven world, concerns about transparency in decision-making processes have reached new heights. Mike Capps, co-founder of Raleigh-based company Howso, is leading the charge for AI transparency, citing the need for fairness and accountability. As AI permeates critical aspects of our lives such as healthcare and education, Capps argues that users should demand the same level of transparency they seek in their breakfast food ingredients.
A major issue with many existing AI systems is their opaqueness, often referred to as black box AI. These systems make important judgments without providing clear insights into the criteria used, leaving users and stakeholders in the dark about the decision-making process.
Howso, formerly known as Diveplane, was founded by Mike Capps in 2018 with a mission to challenge black box AI. The company’s unique approach, known as attributable AI, sets it apart from the rest.
Attributable AI allows users to trace a decision back to specific data points, offering transparency and understandability. For example, Howso’s system can pinpoint the 17 most crucial data points that influenced a medical surgery recommendation, ensuring clarity and accountability.
Howso’s AI engine has found applications across various domains. Collaborating with major retailers, one of its clients, Scanbuy, leverages Howso’s tool for customer intelligence, accurately predicting customer preferences in an explainable manner.
Educational institutions like N.C. State and UNC have also embraced Howso’s technology for specific projects, highlighting the growing demand for transparent AI in academia.
The decision to open-source Howso’s AI engine in September emphasizes the company’s commitment to transparency. This move allows users to design their own explainable AI-driven platforms, further expanding the reach of transparent AI technology.
Howso boasts an impressive client list, including industry giants like Mastercard and Mutua de Madrileña, a Spanish insurance company. The Virginia Department of Behavioral Health and Developmental Services is also utilizing Howso’s technology for enhanced decision-making processes, showcasing the widespread demand for AI systems that prioritize transparency and accountability.
Capps emphasizes the critical importance of transparency in AI, making a parallel with food labels. Just as consumers rely on nutrition labels to make informed choices, individuals should demand transparency regarding AI-driven decisions that affect their lives. Transparency is not only a matter of trust but also a fundamental requirement for responsible software development.
Black box AI, as Capps highlights, poses several inherent problems. It raises concerns about the reliability and accountability of AI systems. Without visibility into the inner workings of an AI system, identifying and rectifying bugs or errors becomes challenging. This lack of transparency also leaves potential unintended consequences or biases unaddressed, leading to significant replacement costs.
One critical area where transparency is vital in AI is in parole decisions. These determinations often rely on historical data, which may contain biases. Scaling up biased data for efficiency can perpetuate unfair and discriminatory outcomes. Capps emphasizes that while streamlining and expediting court processes is desirable, it should not come at the expense of perpetuating racial biases.
As AI continues to shape our lives, the demand for transparency grows louder. Howso’s efforts to tackle black box AI and provide explainable AI systems pave the way for fair and accountable decision-making. Mike Capps and Howso’s mission to prioritize transparency in AI set a positive example for the future of responsible AI development.
