Posted September 13, 2022

How to Eliminate the Specter of Human Bias in AI Applications

Our recent blog discussed the critical gaps businesses must address to achieve Artificial Intelligence transparency, trust, and confidence. It is crucial to address these gaps so your AI ecosystem can be trustworthy.

AI applications ingest training data to learn how to make decisions. But if training data includes biased human decisions or reflects historical or social inequities, then the AI application’s results are flawed and cannot be trusted. There have been numerous instances where AI models were unintentionally used to institutionalize bias, like the one used to predict recidivism but later turned out to be biased against black people. Another example would be the AI recruiting tool that showed discrimination against women.

To make AI trustworthy, companies need to explain the rationale behind an AI algorithm’s results and the accuracy of that algorithm in arriving at an outcome. It requires full transparency so stakeholders can understand and explain the inner workings of their AI systems. Businesses looking to deploy AI but are held back by ethical issues such as human bias should establish conscientious processes to mitigate bias. To do this, companies need to operationalize AI Trust.

Ensure Responsible and Ethical AI by Operationalizing AI Trust

How do you operationalize AI trust? At Konfer, we ensure trust in AI-powered decision-making using our Konfer Confidence Cloud.

Konfer Confidence Cloud is the end-to-end trust management system leader that can operationalize trust of AI applications for organizations delivering on their digital initiatives. It works by mapping, measuring, and managing your AI-powered applications across all stages of solution development, deployment, and production, thereby elevating trust.

Here’s how it works:

Map. You get a global view of your AI assets and their interrelationships. With a unified view and shared understanding of AI inventory, all stakeholders can collaborate more effectively to achieve confidence in their AI initiatives.

We use KonferKnowledge, a repository of all AI software assets and associated attributes, including AI/ML applications, models, feature stores, and data. The KonferKnowledge graph is the single source of truth about all the AI applications, where they exist, what resources they depend upon and share, and what metrics and KPIs they influence for the organization.

Measure. We measure the use of and outcomes of all your AI assets. Konfer empowers you with AI-powered applications with quantified parameters such as fairness, robustness, security, and performance to measure your business risks.

We use KonferConfidence, a quantitative measure that enables businesses to profile and measure AI/ML applications on performance, robustness, privacy, compliance, and regulatory risk factors. Scores are computed using metrics and observations and aggregated over time.

Manage. With a clear path to the truth, all stakeholders can drive actions by initiating reports, incidents, and cases. This way, they can manage their business metrics as outcomes of a trusted AI system.

We use KonferTrust, which generates operational alerts and reports. It works by integrating into an organization’s service management and collaboration systems like Slack for the stakeholders to be alerted to noncompliance and automatically documenting the compliance status of AI/ML applications, models, and data.

Konfer automates the mapping of your AI systems so all stakeholders can readily determine and evaluate the various facets of AI that can generate business risks and confidently manage their business metrics.

You can do more with Konfer Confidence Cloud. Do you want to see it in action? Request a demo today!

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