Agenda

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Troy Schnieder, President of GovExec 360, kicks off the Government & Artificial Intelligence Forum with opening remarks as we embark on a day-long exploration of AI and the key considerations experts are making for its implementation.

Cameron Chehreh of Intel will provide Opening Remarks to the event.

In the past year alone, generative AI has exploded into the public consciousness. With the ability to generate new data similar to any given data set, these algorithms have the potential to revolutionize entire industries. Already, experts are exploring the capabilities in creating seemingly new content, realistic content such as text, training platforms, and more. As with any new technology, there are important considerations to be made before widespread adoption. How are technologists and artificial intelligence experts making sense of this revolutionary moment in AI? In this session, government and industry experts unpack the challenges and opportunities related to generative AI, and how they plan to take full advantage of the latest advancements.

As the world becomes more dependent on our digital networks, disruptions of all kinds are more prevalent, more problematic, and ultimately more anticipated. Hardware malfunctions, software hiccups, network failures, and beyond all have the capacity to interrupt network connectivity but what if this was preventable? In this session, experts in machine learning and artificial intelligence sit down to explore an emerging concept of self-healing networks that provide the ability to predict and even preempt outages and spikes in demand allowing for a proactive and secure enterprise.

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ChatGPT and other generative AI tools are dominating headlines due to their vast potential to address government business challenges. Agency leaders are already exploring what impacts generative AI could have on knowledge management, summarizing customer conversations, and other areas. Yet others are understandably hesitant in implementing the new technology. This session pulls back the curtain on generative AI to better understand how leaders can leverage its value and how to mitigate the potential risks.

The value of data increases exponentially as it is used and reused across the organization delivering on the needs of their mission and vision. The 5Cs - that is, Content, Context, Compliance, Collaborate, Connectivity - when done right in an application domain accelerate the adoption of data practices and enrich and evolve the data culture. Data Fabric (and Data Mesh) are the architecture concepts that makes this complex objective of data integration, information enrichment and knowledge management a reality today. This provides the data practitioner, users and stakeholders access to the right data and decisions at the right time in spite of the underlying complexity of the data sources, infrastructure, network and bandwidth. Learn more about the 5Cs and how the solid foundation of trusted data is essential for performant advanced analytics.

The backbone of every artificial intelligence model is data. As government agencies continue to leverage more data sets than ever before, there are inherent risks to the critical and private citizen data at play. How can security leaders maximize the value of their data integration while protecting against impending breaches? This session explores the security implications involved in the future of artificial intelligence and how agencies are striking a balance between advancements in data management and privacy.

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The inevitable inclusion of AI in critical infrastructure has opened up new vulnerabilities in potential threats. The Department of Homeland Security among other are hot on the case in understanding the problematic features the technology offers. This session explores the potential harms and opportunites to mitigate threats. 

The use of artificial intelligence and machine learning, among other emerging technologies, promises to revolutionize the government industry. AI algorithms can help practitioners work more effectively and make better use of critical data. But the historical data on which these algorithms are built reflect generations of societal biases that can negatively impact minorities. As the use of AI continues to rise, what can leaders do to prevent the perpetuation of these biases and break the cycle of inequities? What similar considerations should leaders be making when balancing the implementation of emerging technologies with the uncertainty of their impact?

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