AiThority Interview with Beena Ammanath, Executive Director at Deloitte AI Institute

Hi, Beena. Please tell us about your role and the team/technology at the Deloitte AI Institute.

Over the course of my career, I’ve served in different technology and data-based roles across industries like manufacturing, financial services, trading, supply chain, and telecom, and have seen AI become mainstream in solving various business problems. I have seen the evolution from traditional transactional database systems to data warehouses and business intelligence to big data, data science, machine learning, and now AI.

AI technology is evolving fast with massive investments into research and think tanks, and the applications of AI are growing at an even faster pace with AI startups, products and evolving challenges around ethics, social responsibility, talent, and the future of work.

In my prior roles, even when I understood my AI use cases, it wasn’t always clear how to make that a reality in the fastest possible way.

For example, could I buy a mature AI product to train on my data and deploy it?

If not, is there a start-up company working on something that I could apply to?

Is there research happening to help me get to a solution faster?

Could I solve my use case by creating a solution in-house, or should I be partnering with another organization?

I realized this is a process most companies go through, and in my experience, no one organization will be able to solve for AI. That’s why, when I came to Deloitte a year ago, I wanted to start the Deloitte AI Institute.

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The purpose of the Deloitte AI Institute is to help enterprise organizations by bringing the best and brightest minds and the entire AI ecosystem in one place to advance research, eminence, and applied innovation across industries. As executive director of the Deloitte AI Institute, I am responsible for blending Deloitte’s deep experience in applied AI with an ecosystem of visionary thought leaders, start-ups, research and development groups, entrepreneurs, investors, and innovators.

In doing so, the Institute will advance the conversation and development of AI to challenge the status quo. By working with some of the smartest people in the field, we aim to deliver impactful and game-changing research and innovation to help our clients use AI across their organization.

As a woman heading AI efforts for Deloitte, how do you motivate other young female professionals to join the movement?

Gender diversity in technology – specifically AI – is lacking. There has been much progress due to STEM efforts in early education to motivate girls and women to take an interest in related fields, and it has been wonderful to see more women pursuing roles in engineering and technology as a result. However, when it comes to AI, I believe there is still much work to be done to develop a more diverse workforce. It is crucial for AI specifically, as the technology impacts all humans and will eventually be incorporated into nearly everything we use – both at work and home. Low-biased, ethical, and fair AI systems require a diverse workforce of humans, including women.

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I’ve been fortunate to be mentored by several women in the field, and they made a significant impression on me and my career. Today, I mentor other women and help them as they progress in AI and technology-focused career paths.

At Deloitte, I co-lead an initiative called Women in Data and AI to help develop the next generation of women leaders in the field. I am also the founder and CEO of a non-profit, Humans for AI, which aims to create an inclusive, diverse AI workforce.

AI is a vast field. Which specialization and techniques are currently part of The Deloitte AI Institute’s ongoing research and development?

The Deloitte AI Institute covers a broad spectrum of AI focus areas on its applications for enterprises across different sectors, with current research and development in the following:

Ethics: We have joined forces with academics and world policy leaders to advance current thinking on AI ethics.

Innovation: We are driving AI innovation and human-machine collaboration in the Age of With.

Global advancements: By examining global challenges to AI implementation and the ways countries are addressing them, we can offer essential leading practices.

The future of work: As AI changes how we work, we are guiding organizations on how to remain distinctly human in a technology-driven world.

AI case studies: We are focused on building ecosystem partnerships, bringing forth insights, and case studies from a variety of industries, universities, and companies.

The COVID-19 pandemic has exposed us to medical and economic uncertainties that none could predict. What do you think about the role of AI should be in such a scenario?

The AI Institute recently released the State of AI in the Enterprise, 3rd Edition, a study examining executives’ sentiments and practices regarding AI technologies.

The study, which was conducted before the pandemic, found that adopters continue to have confidence in AI technologies’ ability to drive value and advantage – and they are increasing their levels of implementation and financial investment. There is a lot of uncertainty around how the COVID-19 pandemic will impact AI investment going forward – with some seeing an acceleration and others predicting a slowdown.

Different analyst firms have varying points of view on how the COVID-19 pandemic will impact AI and IT investment in the next year – some see it growing, others see it flat.

Many enterprises may delay investment because of the uncertainty, others may increase their investment in areas that could provide efficiency gains and reduce costs. Some enterprise technology vendors are publicly stating that they think the pandemic will accelerate the adoption of AI technologies.

In our work, we have seen certain industries increase AI investment, such as the application of AI technologies to health care and education. We also see an increase in demand for applications of AI that provide greater automation and efficiency, for things like supply chains and call centers.

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What is the Future of Work? How are your AI and Automation innovations enabling businesses to grapple with the paradigm shift?

AI and its ability to augment human workers is one of the most influential forces shaping the future of work. We are now in the Age of With, where companies are harnessing the power of “with” to identify unique advantages through analytics and AI.

For example, humans with machines, data with actions, companies with their customers. The results are insights that become automated, engagements that become insightful, and relevant information that can get into the right hands at the right moment.

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We work with our clients to determine what skills and capabilities they need for future success with AI and automation technologies, how their workforce of today relates to their needs of tomorrow, how to access those skills and capabilities, and how to set up internal systems and platforms to enable the continuous adaptation of skills.

At the same time, looking at the importance of a humans-with-machines model, it is crucial that AI and automation tools are closely monitored and reviewed – just like human workers. This introduces a new paradigm into the future of work to make sure that machines are doing their jobs and are adjusted/put on the right path when they’re not.

What is the Future of Digital Transformation? Which technologies are you particularly keen to explore and adopt for your businesses?

Digital transformation has been manifesting itself within organizations for some time. However, as companies continue to mature with their use of more advanced technologies, I feel that true success will be when it’s integrated across entire organizations. For example, right now, AI continues to still be used in pockets within companies – perhaps only in the IT function or for specific applications as they move beyond AI for efficiency or cost reduction into creating new products and services.

True digital transformation will be when AI is integrated across all departments in an enterprise, including finance, HR, marketing, leadership/C-Suite, etc.

Hear it from the pro: Where is Ethical AI Development heading? Any live project examples on Human Emotion/Value loops that you may want to share with our readers?

In our State of AI in the Enterprise, 3^rdEdition survey, 95% of respondents expressed concerns around ethical risks for their AI initiatives. Despite these worries, the study reports only about a third of adopters are actively addressing the risks—36% are establishing policies or board to guide AI ethics, and the same portion says they’re collaborating with external parties on leading practices.

Although there is still a long way to go, a growing number of organizations are tackling AI-related risks head-on:

• As a founding donor for The Council on the Responsible Use of Artificial Intelligence at Harvard’s Kennedy School, Bank of America has embraced the need to collaborate on AI ethics. It has also created a new role—enterprise data governance executive—to lead AI governance for the firm and workwith the chief risk officer on AI governance.
• The German engineering firm Robert Bosch GmbH, which plans to embed AI across its products by 2025, is training 20,000 executives and software engineers on the use of AI, including a recently developed AI code of ethics.
• Workday, a provider of cloud-based enterprise software for financial management and human capital management, is employing a broad spectrum of practices. It has committed to a set of principles to ensure that its AI-derived recommendations are impartial and that it is practicing good data stewardship. Workday is also embedding “ethics-by-design controls” into its product development process.

We are also helping our clients navigate AI ethics with our Trustworthy AI Framework, designed to help organizations navigate through potential issues such as bias, transparency, privacy, and developing regulations.

The Trustworthy AI Framework helps organizations develop ethical safeguards across six key dimensions—a crucial step in managing the risks and capitalizing on the returns associated with AI. These pillars include fair and impartial use checks, implementing transparency and explainable AI, responsibility, and accountability, putting proper security in place, monitoring for reliability, and safeguarding privacy.

Tag a person whose answers you would like to read here:

• Kelley Herod, Deloitte
• Jana Eggers, Nara Logics

Thank you, Beena! That was fun and we hope to see you back on AiThority.com soon.