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C-Suite Perspectives On AI: Dr Jennifer Sample Of Accenture Federal Services On Where to Use AI and…

C-Suite Perspectives On AI: Dr Jennifer Sample Of Accenture Federal Services On Where to Use AI and Where to Rely Only on Humans

An Interview With Kieran Powell

Scale and resource availability: AI is well-suited for tasks that require scalability and efficiency, especially in handling large datasets. Humans often find it challenging to match the speed and consistency AI can provide. For example, I’ve consistently seen analysts overwhelmed with more incidents to investigate than they have time for on any given day. AI can be a powerful tool in triaging and down selecting a priority list for the analyst to review.

As artificial intelligence (AI) continues to advance and integrate into various aspects of business, decision-makers at the highest levels face the complex task of determining where AI can be most effectively utilized and where the human touch remains irreplaceable. This series seeks to explore the nuanced decisions made by C-Suite executives regarding the implementation of AI in their operations. As part of this series, we had the pleasure of interviewing Dr. Jennifer Sample.

Dr. Jennifer Sample PhD is Accenture Federal Services’ Chief AI Growth Officer responsible for supporting federal agency clients in adopting and implementing AI and ML products and services at scale. Sample formerly served as Principal Scientist in the Research and Exploratory Development Department at Johns Hopkins University’s Applied Physics Laboratory. Sample received her B.S. in Chemistry from Pennsylvania State University, her PhD in Physical Chemistry from the University of California, Los Angeles, and MBA from the Massachusetts Institute of Technology.

Thank you so much for your time! I know that you are a very busy person. Our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I always loved science and technology classes in high school, and how science could explain everyday phenomena, such as how batteries work. I grew up in a large family and was a straight-A student and the first to go to college. I always wanted to make a difference for everyday people and achieve my potential. I started out majoring in chemistry and studied Nanotechnology for my PhD. Being part of the excitement around that “next big thing” was addicting!

As my career unfolded, I focused on other emerging technologies which evolved from nano to bio to quantum to AI. Along the way I discovered my leadership and communication abilities, resulting in new career positions. As my roles and impact grew, I began to think I needed to “upskill myself” to achieve goals such “optimizing organizations for innovation” which led me to business school.

I selected MIT due to the data-driven, results-based enterprise focus of the Sloan School of Management and quickly learned from my friends and professors about the inspiring and different ways that one can impact society. I studied analytics and decided to pivot my career focus to consulting to engage with a broader range of clients and address a larger range of challenges through technology and digital transformation. Accenture Federal Services delivers on the promise of technology and human ingenuity which is the perfect description of my own life’s work.

It has been said that our mistakes can be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

Very early in my career as a scientist I remember working on a research proposal for grant funding. My role was to come up with a “game-changing idea.” The proposal’s financial team kept asking me for input. They were probably trying to get me to write a statement of work, but I simply didn’t understand the requirements. I hadn’t realized there are federal acquisition regulations. Without a compliant cost proposal, there is no proposal! The lesson I learned was it takes a team. All parts are important.

Are you working on any exciting new projects now? How do you think that will help people?

Right now, I’m helping to stand up generative AI capabilities in many federal agencies. This involves assessing AI-readiness, identifying use cases, developing guardrails then federalizing the technology in their existing environment or standing up a new one. We are creating tools to help people accomplish tasks more efficiently and effectively. Some examples include:

  • Document drafting to augment the workflow of intel analysts so they can focus their time on data-driven decision making.
  • Smarter chatbots that serve as an interactive set of FAQs so people can get basic questions answered.
  • Assistive coding workflows to accelerate IT and decrease service backlog for people.

Thank you for that. Let’s now shift to the central focus of our discussion. In your experience, what have been the most challenging aspects of integrating AI into your business operations, and how have you balanced these with the need to preserve human-centric roles?

This question is super interesting because I always say, when we get to the heart of a client’s problem, it usually isn’t a technology problem. The necessary technology exists. But to understand why it hasn’t been implemented, the answer is usually some sort of policy, governance, or stakeholder alignment issue. Or the issue could be cultural, something to do with adapting to change or the technology literacy of the workforce. This blend of human and technological solutioning is what I find most rewarding about consulting.

Accenture Federal Services’ adoption of AI into our business is no different because GenAI is so new and took the industry by storm. Many questions needed to be answered including:

  • Who are the right leaders to weigh in on a new policy?
  • What is the process for getting procedures finalized and implemented?
  • How do we adapt AI from one part of our business and use it in another, and who will make those adaptations — existing teams or do we need new ones?
  • Do we need new structures in place to manage, govern, and enforce the responsible use of AI?

These inherently human-centric aspects of integrating AI are the biggest challenges. Without human experts in policy, user experience, security, quality assurance and leaders to bring everyone together to decide on and execute a path forward, the successful adoption of this emerging technology could not get off the ground.

Can you share a specific instance where AI initially seemed like the optimal solution but ultimately proved less effective than human intervention? What did this experience teach you about the limitations of AI in your field?

AI is great in areas with complexity and scale. Can you imagine if it were your job to look at every transaction on everyone’s credit card everyday everywhere, find the fraud, then personally send out text alerts? Even if humans doing that task could result in enhanced accuracy or customer service, which is doubtful, it’s hardly the optimal solution when you factor in employee quality of life and scale of the operations required. We know very well from peer reviewed research that, while humans have intuition and empathy, expert decisions can be affected by factors such as fatigue and unconscious bias. So, depending on the degree of complexity, scale, expertise, and intuition needed, along with the ethical and social implications of the application, we need the right balance of human + AI to perform the task, which may be different from the right balance of human + AI needed to doublecheck the results. In the credit card example, the consumer is the essential human in the loop to verify whatever the algorithm has flagged.

In the federal sector, I recall an effort to deliver an automation tool to reduce arduous manual repetitive tasks. Think filling out forms… We’ve all suffered through entering redundant data on every page when it could have been automatically populated.

However, while the technology can help workers, it is of no use without basic literacy on use cases, exemplars, tech support, change management, and prioritization. So, in the federal example, we had to walk it backwards and provide humans the necessary support to adopt this technology so it became useful and augmented their workflows.

How do you navigate the ethical implications of implementing AI in your company, especially concerning potential job displacement and ensuring ethical AI usage?

From the federal perspective, we anticipate AI to accelerate modernization and augment an already stretched workforce to help reduce backlogs and technical debt, drive data-driven decisions, and introduce capabilities that will enhance government services. From an ethics perspective, Accenture Federal Services has defined Responsible AI mission and principles. We have developed tools, techniques, and policies to mitigate risk and have built them into the systems and platforms that are used.

Could you describe a successful instance in your company where AI and human skills were synergistically combined to achieve a result that neither could have accomplished alone?

We recently hosted a hackathon to encourage our own people to experiment with use AI cases. Interestingly, we were validated when just a few weeks later the executive order and OMB guidance came out encouraging federal agencies to experiment with AI. While many project teams came up with great ideas ranging from public comment document review and summarization to improving task management tools, and have been taking these suggestions to clients, my favorite idea came from our Recruiting team which used AI to help ensure job postings use more inclusive language. This was accomplished by recruiting team members who literally had just learned how to use AI for the hackthon!

Based on your experience and success, what are the “5 Things to Keep in Mind When Deciding Where to Use AI and Where to Rely Only on Humans, and Why?” How have these 5 things impacted your work or your career?

1 . Scale and resource availability: AI is well-suited for tasks that require scalability and efficiency, especially in handling large datasets. Humans often find it challenging to match the speed and consistency AI can provide. For example, I’ve consistently seen analysts overwhelmed with more incidents to investigate than they have time for on any given day. AI can be a powerful tool in triaging and down selecting a priority list for the analyst to review.

2 . Complexity and repetition: AI excels in repetitive and data-intensive tasks, while human judgement is more suitable for complex, nuanced situations. As an example, Accenture Federal Services embedded generative AI capabilities in our Next-Gen Mission Analytics (NMA) platform, which is an open-source intelligence platform delivering near real-time pattern and behavioral analysis of more than 100,000 global media sources through a common operating picture. The generative AI interface enables a natural language query to create custom, on-demand visualizations from millions of open-source documents. As a result, the hours analysts spend researching, finding topics, translating, and structuring queries are now reduced to minutes.

3 . User interaction and empathy: In roles that involve direct user interaction, empathy, and understanding, like HR for example, humans outperform AI. Tasks like counseling or customer service can benefit from the human touch, where emotional intelligence makes a difference. I frequently see this in play when working with clients on their modernization journeys. I find out what their biggest pain point is, then to ask the question, “why hasn’t this problem been solved yet?” This discovery process is critical to formulating a plan to solve the problem, yet it really requires getting to know the client, their mission, and spending time face-to-face to get a real understanding of the issue. I recently met with a client who was very interested in sophisticated mobile analytics but was having trouble adopting mobile device technology because they couldn’t issue enough phones. We came up with a solution that involved using personal mobile phones and defined a successful path forward.

4 . Human expertise and intuition: Humans possess critical thinking and creativity which are often crucial in ambiguous and novel situations. AI may lack the ability to navigate uncertainties and handle unique scenarios that human expertise provides. As an example, federal leaders need to make informed, data-driven decisions on multifaceted issues such as conflicts, crises, and disaster response by combining essential human judgment with models and simulations. We develop the technology to support clients with the ability to assess potential scenarios on diplomatic missions and create a model of likely outcomes for consideration. Generating potential outcomes provides valuable input that human leaders can consider, in addition to their intuition, about a given topic thus increasing confidence in the recommended course of action.

5 . Ethical and social impact: AI lacks moral reasoning and a deep understanding of social context making human judgement crucial for ethical considerations and sensitive interactions. Also, there are certain applications where we as humans simply may never accept AI without a human in the loop. That’s why, at Accenture Federal Services, our teams keep Responsible AI top of mind, designing, developing, and deploying AI with good intention, engendering trust, and scaling AI with confidence.

Looking towards the future, in which areas of your business do you foresee AI making the most significant impact, and conversely, in which areas do you believe a human touch will remain indispensable?

I expect the human touch will always be indispensable in leadership and strategy, which are required anywhere people must work together to achieve a common goal in ambiguous and complex circumstances. AI lacks the empathy and emotional intelligence which is necessary in effective leadership. Additionally, when it comes to ethical decision-making, we will not be able to rely on AI anytime soon. Human ethical and moral considerations involve a depth of understanding that AI doesn’t grasp at this time.

That said, AI is excellent at better optimizing supply chains and the so-called “N-tier” dependencies. Robotics and automation are already crucial components of manufacturing and production. AI will increasingly power improved quality control and error reduction. AI will also enhance the quality of customer service, which may seem paradoxical, but we are already using virtual assistants and chatbots to free up humans for more complex or nuanced needs. So, improved AI will enhance the efficiency and efficacy of this loop. Finally, the biggest impact I see with AI is making federal agencies more data-driven and insightful, enabling the rapid processing of vast amounts of data on a variety of topics.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂

I’d love to see AI level the socioeconomic playing field. I believe that equitable access to education, networks, funding, and resources to support entrepreneurs around the globe with social and environmental missions would create positive and sustainable impact in areas like poverty, education, healthcare, and the environment. I’d love to see marginalized or fringe ideas that typically don’t get executed start to get off the ground using the power of AI.

How can our readers further follow your work online?

This was very inspiring. Thank you so much for joining us!

About The Interviewer: Kieran Powell is the EVP of Channel V Media a New York City Public Relations agency with a global network of agency partners in over 30 countries. Kieran has advised more than 150 companies in the Technology, B2B, Retail and Financial sectors. Prior to taking over business operations at Channel V Media, Kieran held roles at Merrill Lynch, PwC and Ernst & Young. Get in touch with Kieran to discuss how marketing and public relations can be leveraged to achieve concrete business goals.

C-Suite Perspectives On AI: Dr Jennifer Sample Of Accenture Federal Services On Where to Use AI and… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.