AI Watch

AI Watch: Stanford's Annual AI Index Reveals Top Trends

This week, Stanford University's Institute for Human-Centered Artificial Intelligence (HAI) released the highly anticipated seventh edition of its annual report on AI trends ("Artificial  Intelligence Index Report 2024"). The index tracks, collates, distills, and visualizes data related to AI, and it helps to make the rapidly evolving world of AI more generally accessible.

There's a lot to like in this report, including the research team's powerful mission statement:

"Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI."

This year there are more eyes on this report than ever, and I thought it would be useful to underscore three insights you won't want to miss:

  • Industry is leading academia in model development: This echoes my own experience. We are seeing a new interest in investing and building AI systems by the industries that need it most. Especially in finance and healthcare, we are seeing industry drive innovation and research, while academic research is lagging. This makes sense to me, as AI is becoming more accessible and economical; companies don’t have to wait for academic research. I'm also seeing organizations invest in private research teams, rather than collaborating with academic institutions. I'm excited to report that the number of industry and academic collaborations reached an all-time high this year, and I see more of that in our future.
  • AI regulation in the US is on the rise, and the US leads the world in AI Model Development: We saw a 50% jump in AI regulation in the past year. We also saw regulation appear at local, state, and federal levels. The Executive Order was released by the White House last month set some clear guidelines for government agencies, but also US companies, to help navigate the complexities arising from fast-paced of innovation. I get asked often what country is leading the race in AI. If you use the metric of models in production, the US is leading with 61 notable models being deployed.
  • AI helps workers to be more productive and leads to higher quality work This observation is a highlight for me personally. As companies begin to navigate the world of AI, they're often looking for quick wins. One way to start seeing a positive impact on your business is to educate your workforce on how to use the AI that is rapidly showing up in the tools they use every day. At the AI Leadership Institute, we did our own survey and found that 70% of workers who received training saw an immediate boost in productivity and an increase in higher value work. This is such an important step that I created an Upskilling Guide for the teams that I work with help them get a jump start on this new, but required, skillset.

Among other things, this report crystalized much of what I experienced earlier this year after participating in the "Foundation Model Scholars Program," one of the inaugural executive workshops offered by HAI. The workshop provided access to decades-old research that led to the technologies in and surrounding Generative AI, and it gave me and my team insights that allowed us to see ahead of the curve and anticipate what's coming next. It also fueled many of the successful deployments I was part of, and now we can see those patterns emerging at scale.

The report is free, and I strongly encourage you to read it.

This week I also had the chance to speak to the National Association of Broadcasters about the importance of measuring the benefits and the risks when deploying GenAI. As you can imagine, misinformation, fake news, and deepfakes were a big part of the conversations, especially in an election year. There were hundreds of new and incumbent companies sharing how they have evolved their products and services with AI. Check out the NAB keynote for a unique perspective from the world of broadcasting!

Until next time, embrace the world of learning by doing, and share what you are learning as you try out new AI features in the products you use every day! As always, connect with me on LinkedIn with any questions, feedback, or ideas for an article.

Posted by Noelle Russell on 04/16/20240 comments

AI Watch: Leading Safe AI System Development--Research, Policy, and Engineering

This past week I had the opportunity to witness the progression of AI excitement across three separate and distinct pathways.

First, in my time with the executives at the ACHE 2024 Congress on Healthcare Leadership in Chicago, I delivered one of the opening keynotes and shared some of the exciting advancements that are making the lives of healthcare practitioners better and more efficient. As many of these healthcare companies are beginning to experiment with AI solutions, I reminded them that going from the playground to production would not only require new technology, but also a new mindset. During the Q&A I got two great questions, and I wanted to share my answers with you:

Question: What is the most exciting thing you've experienced in healthcare and AI?

Answer: I've seen rapid advancement of the use of AI in the healthcare industry and one of my favorite use cases is the development of personalized medicine and advancing patient-centered care. Imagine a world where we combine what we're learning from companies like 23andMe with predictive analytics to help us craft highly tailored personalized treatment plans. We have more data about our biological and physiological makeup that we can now use to create better treatment options personalized by demographic, and sociographic elements.

Question: What are you most worried about? 

Answer: I often get this question across industries like finance and healthcare. As a mom of a child with special needs and a caregiver to my dad who suffered a traumatic brain injury, I worry that technologists are beginning to enthusiastically build solutions in healthcare that might unintentionally perpetuate and amplify bias that leads to the creation of systems that generate unfair outcomes. I'm so worried about this, that I now offer services that safeguard generative AI applications as we move from the playground to production. Microsoft recently launched a set of tools that will make this accessible to every organization. I’ll share more about this in a moment.

Also, Adobe held its annual Adobe Summit 2024 in Las Vegas this week. I was an Adobe AI Insider and had a chance not only to get front row seats to the amazing keynotes, but also have direct one-on-one Q&A time with some of the Adobe Digital Executives. Here are a couple announcements I'm most excited about:

Adobe announced GenStudio for creating marketing assets at scale with the help of AI. They revealed new and specialized tooling to help creatives spend more time creating and less time on the routine tasks that often fill a creative’s day as they roll out what they have created to the world.

Microsoft and Adobe announced the integration of Adobe Experience Cloud workflows and insights with Microsoft Copilot for Microsoft 365 to help marketers overcome application and data silos and more efficiently manage everyday workflows. Imagine being able to get Generative AI to help with the creation of your brief for a new campaign and have that brief help you create consistency across executive reviews, assets, reports, and messages. Insight integration across Microsoft Teams, Word and PowerPoint means less hopping around across tools to get the work done, allowing marketers and creatives to do more in less time. Let’s hope the time they save allows them to think and be more creative and we don’t fill those new-found hours with meetings instead.

Finally, I had the unique opportunity to meet with Microsoft's Responsible AI team last week in New York to test drive their new tooling for helping organizations safeguard their AI systems. I was asked to be a part of this exclusive workshop because I'm a Microsoft AI MVP and I offer AI Red Teaming services through my company, the AI Leadership Institute. One of my key takeaways from this event was the way the team was structured, and I think every company can learn something from this.

Three Microsoft executives participated in the workshop: Sarah Bird, Chief Product Officer of Responsible AI; Natasha Crampton, Chief Responsible AI Officer; and Hanna Wallach, Partner Research Manager. Together, these leaders establish a kind of three-legged stool for responsible AI at scale. You need someone who leads engineering, someone who owns policy and governance, and someone who spearheads the research side of the organization. This team announced updates to the tooling to help teams build better and more robust safety systems for their Generative AI applications.

As you begin to go from AI playgrounds to production, remember to consider not only the enthusiastic part of AI, but also how you are safeguarding these solutions for safe and equitable outcomes for everyone involved. AI Red Teaming can help you go from enthusiasm to execution responsibly. Next time we will dive into how to build a safety system for your generative AI applications. As always, connect with me on LinkedIn to learn more about what's happening in responsible AI around the globe.

Posted by Noelle Russell on 04/02/20240 comments

AI Watch: Five Strategies for Building Responsible AI at Scale

This week I'm attending the Microsoft Global MVP Summit. The event provides MVP awardees with an annual opportunity to connect with each other and with Microsoft Product Leadership to talk about the future of technology and developer experience at the company.

While much of what was discussed is still under NDA (non-disclosure), I can share some themes that I found interesting as the race to responsibly use AI at scale continues. I have summarized 5 key messages from my week with like-minded experts and innovators leading product development.

Year of the Agent
2023 was the year of the Chatbot (renewed) and 2024 is the year of the Agent. An Agent is a purpose built, autonomous AI solution that operates within the bounds we give it. Last month, Microsoft announced the public preview of the Assistants API that enables the creation of high-quality copilot/generative experiences inside applications. This is interesting because it's the first of a series of capabilities aimed at giving developers the ability to integrate generative AI into any application more easily. Imagine building an insurance application with this new API, and then being able to offer customers a real-time conversational interface that can call and execute actions autonomously. You could set rules and thresholds that allow certain types of transactions to be facilitated by an agent that can call other agents and APIs and orchestrate an entire workflow with natural language.

Multi-task Orchestration
Over the past 6 months I've been working with executive teams to evolve their thinking around responsible AI at scale. Rather than focusing on building that killer app, or a single use case, we need to shift our thinking to how to orchestrate models together. I call this multi-task orchestration. In a recent executive workshop, a client shared that they have more than 900 unique use cases that they need to consider and prioritize. I led them through an exercise that helped them pick the right project at the right time with the right model. We also focused on selecting use cases that would create opportunities to unlock more value over time, rather than focusing on a single use case that couldn’t be built upon. The next year will bring more sophistication in how we use both large and small language models to solve the right problem at the right time for the right customer as cost effectively as possible.

Responsible AI
Another key theme of the summit was advancements in the tooling offered by the Responsible AI team at Microsoft. There are several ways to think about your strategy to build responsible AI solutions at scale. Here are some principles to consider: Transparency, Fairness, Trust, Reliability, and Explainability. I'll have more to say about these in future posts. If you can’t wait to dive in, you can check out this article from Microsoft on the ABCs of Responsible AI.

Safe Deployments are All About Risk
In the world of generative AI, the quickest way to fail is to blindly launch your solutions without weighing the risks involved. The list of risks you should consider includes grounded output errors (hallucinations), jail breaking attempts, prompt injection, copyright infringement, and manipulation of human behavior (deep fakes, for example). With these risks in mind, you'll want to establish a red team, something that my company offers as a service, or creating one for your own AI efforts. This can help you identify risks, measure their potential impact (for prioritization), and mitigate risks in the system. You can expect to see more and more tools designed to help these team become more effective this year.

It's All About the Builders
It was very exciting to see the tools and resources that are being released for AI builders. I've had to navigate across so many Microsoft studio products over the years, that I have a separate folder dedicated to the bookmarks to keep them all straight. Thankfully, Microsoft felt our collective pain and launched a single AI studio this year. Azure AI Studio, currently in beta, combines the development tools needed to build generative AI applications with a unified studio for all the other Azure AI services, such as speech and computer vision.

Another tool that's available now is Microsoft's Human-AI Experience (HAX) Toolkit. Developed through a collaboration between Microsoft Research and Aether, Microsoft's advisory body on AI Ethics and Effects in Engineering and Research, the Toolkit was designed for teams building user-facing AI products. It was developed specifically to help developers conceptualize what an AI system will do and how it will behave. I recommend using it as early in your design process as you can.

In this fast-moving world of generative AI, it’s critical to be mindful of our approach. Remember the three keys to any responsible AI solution, build it so it can be Helpful, Honest, and Harmless. 

It's been a fun week in Redmond, and I can’t wait for Microsoft BUILD in May!


Posted by Noelle Russell on 03/14/20240 comments

AI Watch: The House that AI Built

This week I'm presenting at the International Builders' Show, the largest annual light construction conference in the world. NAHB, the organizer, expects to attract nearly 70,000 visitors from more than 100 countries to Las Vegas for this event. I'm appearing on the Game Changers track, and I'll be talking about how artificial intelligence is quickly becoming a game-changing technology in home building. Chances are many of the conference attendees are already feeling the influence of AI, but I'm going to be presenting use cases that underscore the innovative ways AI will be changing the world of home building. I'd like to share three examples here:

Welcome to AI Watch

Welcome to the inaugural post of our new "AI Watch" blog, written by Noelle Russell, Microsoft MVP and founder and Chief AI Officer at the AI Leadership Institute. An expert in the Azure Machine Learning Platform and  Azure AI Services, Noelle specializes in helping companies with emerging technologies, cloud, AI and generative AI. You can find her on X at @NoelleRussell_.

Smart Home: Some of us have been anticipating the maturation of the smart home for about a decade. It's been a long trip, and the road has been a bumpy one, but we're getting there. We now have smart thermostats, smart lightbulbs, and vacuum cleaners that know more about the nooks and crannies of our homes than we do. And we have smart speakers that get smarter with every generation. New home buyers are looking for residences that are equipped with interconnected devices and systems that can be controlled and automated through a central hub or smartphone app.

Speaking personally, smart-home tech has been a blessing to me and my family. I have a son with Down Syndrome and a father who suffered a traumatic brain injury, and their needs have motivated me to find, test, and deploy AI-enable home solutions to make their lives better. I have more than 100 AI-enabled devices in my home, and I've tested dozens more. I'm closer to the cutting edge than most homeowners, but not by much, and the gap is closing, fast. In the future, builders will find ways to integrate technology into homes in contextually appropriate ways that will drive increased sustainability and satisfaction of the homeowners.

Digital Twins for Home Building: Virtual objects known as "digital twins" have found their way into the home construction industry, and generative AI has become a critical enabler of this technology. GenAI can be used to create fully immersive virtual homes that builders can "walk through" as they make decisions about designs and materials. Builders can simulate different design options and evaluate their performance before they've driven a single nail, reducing—sometimes drastically—the need for costly changes during construction. 

Virtual twins can ingest a vast amount of data and use it to replicate processes that predict potential performance outcomes and issues that might not be obvious in the real-world. They can simulate the performance of various sustainable materials and construction techniques. They can make it possible to analyze data about bio-based materials, passive solar designs, and plans for natural light, and then incorporate that data into building plans.

Productivity: One of the greatest potential limiters of growth in construction is productivity. While other industries are increasing their ability to produce, in construction that ability is declining. According to Fannie Mae, we will be about 400 million units short of the needed inventory of housing in the US over the next decade. AI-based technologies can help construction companies connect designers with contractors and builders, reducing the friction currently associated with mass producing housing units. AI can be used to analyze regulation in real time to offer insights that help construction companies build the right thing, at the right time, under certain regulations. AI can be the amplifier of productivity that the industry has been so hungry for.
The explosion of AI-based technologies and solutions is fueling an urgent need to rethink how homes are built. AI empowers us to reinvent the way we mass produce homes in a responsible, economical, and sustainable way, allowing us to meet the shortage of homes with growing productivity and increased outputs.

Join me next time when I will share the latest from my trip to the Microsoft Global MVP Summit.

Posted by Noelle Russell on 03/01/20240 comments