Charles Lyons-Burt
David Egts is a lifelong engineer and software expert who has garnered accolades throughout his career, with significant stints at Concurrent Technologies Corporation, Silicon Graphics and Red Hat. He spent 15 years at the latter company, completing his tenure as its chief technologist and senior director of the North American public sector business.
Egts came to Salesforce’s MuleSoft in 2022 as its inaugural public sector chief technology officer, wherein he liaises with high profile federal government leaders to encourage the seamless adoption of his organization’s automation applications. He also works to inform the product creators and researchers of government customers’ needs, ensuring an effective feedback loop. In addition, Egts is among Executive Mosaic’s esteemed GovCon Experts.
In this Executive Spotlight interview, Egts spoke with ExecutiveBiz about what he sees as the immense benefits of artificial intelligence, the ethical guidelines organizations must consider during adoption and his thoughts about the market reception of the rise in AI interest.
Tell us about the current state of the artificial intelligence market. Where are you seeing new opportunities in AI and where do you think the market is heading?
AI, particularly generative AI, has captured the imagination of not only technologists but also the mainstream, the boardroom and government leaders. Line of business leaders yearn to harness the promise of AI to gain competitive advantages through increased productivity, efficiency and creativity. Chief information officers and chief information security officers are assisting lines of business by helping them distinguish between hype and reality and plan to embrace AI while addressing the near- and long-term risks associated with any new technologies. Much of the mainstream discussion of AI focuses on the consumer and private sectors. Still, AI can enhance public sector service delivery in various ways:
Citizen experience: AI can personalize citizen experiences by integrating disparate data sources, recommend services tailored to their needs and optimize the delivery of government services.
Healthcare delivery and research: AI can help develop new drugs and treatments, diagnose diseases and provide personalized care to patients.
Fraud, waste, and abuse: AI can detect fraud, manage risk and identify opportunities for process optimization that lead to improved logistics and service delivery.
Cybersecurity: AI can detect and prevent cyberattacks and analyze software supply chains for tampering.
Can you talk about the importance of AI ethics? Explain why we should be paying more attention to ethical AI.
Many organizations are developing AI technologies at warp speed with a startup mentality of ‘move fast and break things.’ The public sector, and the private sector organizations that support them, can’t move this fast, as ‘breaking things’ could be catastrophic given the impact governments have on our lives, society, and the world we live in. As such, agencies need to develop AI responsibly and ethically and only partner with private sector companies that transparently adhere to commonly-held principles. Salesforce, for example, has five guidelines for generative AI:
Accuracy: We need to deliver verifiable results that balance accuracy, precision and recall in the models by enabling customers to train models on their own data.
Safety: As with all of our AI models, we should make every effort to mitigate bias, toxicity and harmful output by conducting bias, explainability, robustness assessments and red teaming.
Honesty: When collecting data to train and evaluate our models, we need to respect data provenance and ensure that we have consent to use data (e.g., open-source, user-provided).
Empowerment: There are some cases where it is best to fully automate processes, but there are other cases where AI should play a supporting role to the human — or where human judgment is required.
Sustainability: As we strive to create more accurate models, we should develop right-sized models where possible to reduce our carbon footprint.
In which applications are you seeing the highest demand for AI/machine learning, and can you explain what’s driving that demand?
I see the highest demand for AI/machine learning in the generative AI space to improve worker productivity and how business gets done. Generative AI will profoundly affect the future of work — it won’t just enhance work but transform it fundamentally.
This may sound scary to many, as they might fear their jobs being replaced. Instead of replacing jobs, generative AI will enhance the productivity of workers and organizations that embrace it. The camera didn’t replace the painter, and the synthesizer didn’t replace the violinist. These new tools made better and more prolific artists and musicians, and more of them. AI has the potential to do the same thing.
An example of this trend is the emergence of ‘co-pilots’ that ride alongside workers to help create and refine documents, graphic designs and code, deliver tailored customer service and so much more. Human intervention remains necessary, but to varying degrees and at varying points in the process. For instance, a human editor may fact-check and refine AI-generated meeting summaries and action items before being used. In other cases, such as a non-designer relying on AI to design website graphics or an email layout, the feedback may be binary — accepted or not. In more advanced applications, AI can play a collaborative role, helping experts automate the lower-level tasks of a project while their creativity is focused on the more sophisticated challenges.
