The State of AI

Recent reports on the state of Artificial Intelligence

Image: ThisisEngineering / Pexels.

What follows is a set of recent reports that assess the ‘state of AI’ for discussion purposes. The past five years have delivered impressive advances and, as captured in the about section, AI is no longer a frontier technology, though it still qualifies as emerging tech… with all of what that entails in the fluid world of innovation, as pressing challenges happen to be commonplace.

Image: The State of AI in 2021, McKinsey.

“Findings from the 2021 survey indicated that AI adoption is continuing its steady rise (…) up from 50 percent in 2020.”

“The business functions where AI adoption is most common are service operations, product and service development, and marketing and sales, though the most popular use cases span a range of functions.”

“The top three use cases are service-operations optimization, AI-based enhancement of products, and contact-center automation, with the biggest percentage-point increase in the use of AI being in companies’ marketing-budget allocation and spending effectiveness.”

“The companies seeing the biggest bottom-line impact from AI adoption are more likely to follow both core and advanced AI best practices, including MLOps; move their AI work to the cloud; and spend on AI more efficiently and effectively than their peers.”

Chui, Michael et all. The State of AI in 2021. McKinsey. December 8, 2021. Accessed February 1, 2022.

Image: State of AI Report 2021, N. Benaich and I. Hogarth.

“AI is stepping up in more concrete ways, including being applied to mission critical infrastructure like national electric grids and automated supermarket warehousing optimization during pandemics.”

“Investors have taken notice, with record funding this year into AI startups, and two first ever IPOs for AI-first drug discovery companies, as well as blockbuster IPOs for data infrastructure and cybersecurity companies that help enterprises retool for the AI-first era.”

Benaich, Nathan and Hogarth, Ian. The State of AI Report. October 12, 2021. Accessed February 1, 2022.

Image: Deloitte.

“Organizations that document and enforce MLOps processes are twice as likely to achieve their AI goals. They’re also nearly twice as likely to report being extremely prepared for risks associated with AI.”

“Becoming an AI-fueled organization is to understand that the transformation process is never complete, but rather a journey of continuous learning and improvement.”

“The risks associated with AI remain top of mind for executives. We found that high-achieving organizations report being more prepared to manage risks associated with AI and confident that they can deploy AI initiatives in a trustworthy way.”

State of AI in the Enterprise Fourth Edition. Deloitte. October 231, 2021. Accessed February 1, 2022.

Image: HAI Stanford University.

“Generative everything: AI systems can now compose text, audio, and images to a sufficiently high standard that humans have a hard time telling the difference between synthetic and non-synthetic outputs for some constrained applications of the technology.”

“The industry shift continues. In 2019, 65% of graduating North American PhDs in AI went into industry—up from 44.4% in 2010, highlighting the greater role industry has begun to play in AI development. AI has a diversity challenge: 45% new U.S. resident AI PhD graduates were white—by comparison, 2.4% were African American and 3.2% were Hispanic.

“Though a number of groups are producing a range of qualitative or normative outputs in the AI ethics domain, the field generally lacks benchmarks that can be used to measure or assess the relationship between broader societal discussions about technology development and the development of the technology itself.”

2021 AI Index Report. HAI Stanford University. Accessed February 2, 2022.

Image: AI100 2021 Study Panel Report

“An overarching and inspiring challenge (…) is to build machines that can cooperate and collaborate seamlessly with humans and can make decisions that are aligned with fluid and complex human values and preferences.”

“AI approaches that augment human capabilities can be very valuable (…). An Ai system might be better at synthesizing available data and make decisions in well characterized parts of a problem, while a human may be better at understanding the implications of the data (…). It is increasingly clear that all stakeholders need to be involved in the design of AI assistants to produce a human-AI team that outperforms either alone.”

“The core technology behind most of the most visible advances is machine learning, especially deep learning (including generative adversarial networks or GANs) and reinforcement learning powered by large-scale data and computing resources. GANs are a major breakthrough, endowing deep networks with the ability to produce artificial content.”

“With the explosion of information available to us, recommender systems that automatically prioritize what we see when we are online have become absolutely essential. Such systems have always drawn heavily on AI, and now they have a dramatic influence on people’s consumption of products, services and content.”

“A major area of opportunity for augmentation is for AI-based methods to assist with decision-making (…) ongoing research seeks to determine how to determine how to divide up tasks between the human user and the AI system, as well as how to manage the interaction between the human and the AI software (…) to produce a human-AI team that outperforms either alone.”

“At the end of the day, the success of the field will be measured by how it has empowered all people, not by how efficiently machines devaluate the very people we are trying to help.”

Littman, Michael et all. Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. Stanford University. September 2021. Accessed: February 7, 2022.

Put Humans at the Center of AI

Image: MIT Technology Review

“We need to be much more human-centered. If you look at where we are in AI, I would say it’s the great triumph of pattern recognition. It is very task-focused, it lacks contextual awareness, and it lacks the kind of flexible learning that humans have. We also want to make technology that makes humans’ lives better, our world safer, our lives more productive and better. All this requires a layer of human-level communication and collaboration.”

Introduction to Stanford Human Centered Artificial Intelligence.

“More jobs will be related to artificial intelligence, so we need a huge workforce, and we need a more inclusive base. That’s an economic argument. There are also tons of studies that have shown that when a diverse group of workers come together, the solutions they find in their work are more innovative and more creative. That drives innovation. But it’s also moral and ethical.”

Knight, Will. Put Humans at the Center of AI. MIT Technology Review. October 9, 2017.

Exercising Design Foresight and the Future of AI Products & Services

Human Centered AI and Digital Transformation

Additional information and registration link available on innovarista.org – Human Centered AIOps.

Making the Case for Human Centered AI

I have made new additions to the ‘about‘ section, which now features insights from Gartner, IDC, McKinsey, MIT and The Economist.

At the bottom of that page you will also see an update reflecting the following Quality eXperience by Design (QXbD) principles for Human Machine Systems (HMS) involving AI:

  • consistently safe and ethical
  • empathic, ergonomic and accessible
  • outcome oriented, value driven and highly efficient
  • easily operable, agile, optimizable and serviceable
  • resilient, responsive, respectful and responsible
  • transparent, observable, traceable and explainable
  • acceptable, auditable and accountable

Nokia Bell Labs’ Future Human

“New wireless generations come in 10 year cycles. Nokia Bell Labs has already started 6G research ahead of its arrival in 2030s. But what is 6G and what is involved in getting there?”

“6G will connect the human and digital worlds. It will enable us to make holographic calls. It will include sensing capabilities that will enable us to see around corners.”

Vetter, Peter. Nokia’s Vision for the 6G Era. Nokia Bell Labs, January 20, 2022. Accessed February 2, 2022.

Image by Nokia Bell Labs.

“It’s easy to think of human augmentation as an intimate physical technology: a prothesis to replace a limb or a surgical procedure to correct a physical deficiency. But Nokia Bell Labs believes in a Homo Augmentus future that reaches far beyond the confines of the human body, giving us control of robots and devices that become remote extensions of ourselves.”

“Augmentation won’t just compensate for disabilities; it will enhance our physiologies and monitor our bodies. Augmentation will no longer be limited to physical tasks; it will increase our cognitive abilities and memory, enhancing our minds as well as our muscles.”

Eggleston, Michael. Introducing Homo Augmentus. Nokia Bell Labs. October 27, 2020. Accessed February 2, 2022.

Image by Nokia Bell Labs.

“We sit at the cusp of a dramatic augmentation of human intelligence driven by [three pillars:] mathematical advances in representation, machine learning models and algorithms for prediction and communication technologies that both amplify our natural human abilities and extend them beyond traditional human traits.”

“In addition to the optimization of mundane tasks, this sea of data will be used to yield solutions to increasingly complex problems. These solutions will not only be automated actions designed to replace humans, but will instead include a broad array of assisted thinking tools that enable humans to gain better understanding from the data and to predict future outcomes. This step change in human intelligence will enable all humans to work in perfect coordination with these tools, further driving the cycle.”

“In recognizing this cycle, we see that transformative research driving step changes in one pillar* lead to step changes in the other two pillars. Conversely, neglecting research in one pillar can seriously slow progress in intelligence augmentation (…) augmenting human intelligence requires research into each of the three pillars.”

Kennedy, Sean and White, Christopher. The Future of Augmented Intelligence. Bell Labs Technical Journal., Volume 25. December 2020.

Image by Nokia Bell Labs.

“Welcome to Future Human, where we explore the human potential of technology. Much of the technology we take for granted was conceived over decades, forged by an ongoing collaboration between researchers, artists and the keenest engineering minds in the world.”

“As the science fiction of days past becomes everyday reality, where will the next great ideas come from? Listen in as today’s most adventurous and creative thinkers unleash their ideas for a more connected, productive and humane world. Future Human is a presentation of Nokia Bell Labs, produced by audiation.fm.”

Podcast available on Apple and Spotify.

Interview on HC AI and Making Tech Human at Emotion Tech 2021

Human Centered Artificial Intelligence

Source post on innovarista.org – Emotion Tech Forum’s Interview Recording.

Industry 4.0 is People Powered

The Fourth Industrial Revolution

Source graph: Darwin Peacock, Maklaan on Wikipedia.

“While Industry 4.0 is still evolving (…) companies who are adopting the technologies realize its potential. These same companies are also grappling with how to upskill their current workforce to take on new work responsibilities (…) and to recruit new employees with the right skills.

“Automation (…) with smart and autonomous systems [is] fueled by data and machine learning (…) a combination of cyber-physical systems, the Internet of Things and the Internet of Systems make Industry 4.0 possible and the smart factory a reality.”

“As a result of the support of smart machines that keep getting smarter as they get access to more data, our factories will become more efficient and productive and less wasteful (…) ultimately, it’s the network of these machines that are digitally connected with one another and create and share information that results in the true power of Industry 4.0.”

Marr, Bernard. What is Industry 4.0? Here’s A Super Easy Explanation For Anyone. Forbes. September 2, 2018.


Picture source: Cristina Morillo on Pexels.

“More than 70% of companies are still stuck in pilot purgatory (…) companies at the forefront of the technology frontier are empowering their workers with digital technologies—and the skills they need to use them.”

“Over the last several years, research with the World Economic Forum, in collaboration with McKinsey, surveyed thousands of manufacturing sites on their way to digitizing operations (…) keeping people at the center is actually pretty straightforward because people are the number-one priority in operations.”

“First make sure the workforce is engaged. Make sure the infrastructure is ready so that you don’t run into roadblocks. And then really prioritize. Pick use cases that are going to have a big impact. As the team says, “Think big, start small, and then scale fast.”

Luchtenberg, Daphne. The Fourth Industrial Revolution Will Be People Powered. McKinsey & Company. January 7, 2022. Podcast.

Global Lighthouse Network. World Economic Forum. Accessed January 10, 2022.

Webinar on Human-AI Teaming: State of the Art and Research Needs

Human Centered AI

Picture source: Eventbrite’s webinar registration site.

“Although artificial intelligence (AI) has many potential benefits, it has also been shown to suffer from a number of challenges for successful performance in complex real-world environments such as military operations, including brittleness, perceptual limitations, hidden biases, and lack of a model of causation important for understanding and predicting future events.”

“These limitations mean that AI will remain inadequate for operating on its own in many complex and novel situations for the foreseeable future, and that AI will need to be carefully managed by humans to achieve their desired utility.”

Human AI Teaming Report – “This activity was supported by contract number WBSRA-21-10-NAS between the National Academy of Sciences and the Wright Brothers Institute as a subcontractor to the Air Force Research Laboratory (…) also supporting the Committee’s work are the Board on Human-Systems Integration core sponsorship grants with the National Aeronautics and Space Administration, US Army Research Laboratory, the Human Factors and Ergonomics Society, and the Society for Human Resource Management.”


“The Board on Human-Systems Integration will host this session on January 13, 2022 at 1:00 pm ET for a public webinar on a new report from the National Academies of Sciences, Engineering, and Medicine.”

“Human-AI Teaming: State-of-the-Art and Research Needs examines the factors that are relevant to the design and implementation of AI systems with respect to human operations. This report provides an overview of the state of research on human-AI teaming to determine gaps and future research priorities and explores critical human-systems integration issues for achieving optimal performance.”

“The webinar will be presented by members of the report’s authoring committee and will include an overview of the study process and discussion of the report’s research objectives for human-AI teaming for the 711th Wing of the Air Force Research Laboratory.”

Human-System Integration (HSI) Processes for Human-AI Teams.


Thanks: Mica Endsley, Cognitive Engineering and Decision Making Technical Group at the Human Factors and Ergonomics Society.

TimBL’s Social Linked Data

Tim Berners-Lee needs no introduction. I would like to take this chance to thank PMI for connecting the dots, making introductions and setting up last year’s discussion on what’s next for the world of data and AI.

We approached the subject from a human centered standpoint, so that the conversation would focus on both value and challenges in a new brave world where reality and virtual environments showcase new behaviors, conducts and fast evolving cultural norms…

…jointly with a pressing need for clearly identifying, rather than obscuring, the nature and property of digital things. Big data, blockchain, Non Fungible Tokens (NFTs) as well as recommendation engines in smart contracts being part of today’s mix. TimBL shared his vision on web decentralization and Social Linked Data (SOLID) which is implemented by Inrupt:

“Solid is a technology for organizing data, applications, and identities on the web. Solid enables richer choices for people, organizations and app developers by building on existing web standards.”

“Users control which entities and apps can access their data. Apps can access rich stores of data from any Pods, with user permission. Pods store use data in an interoperable format and provide users with permissioning controls.”

Driving AI with QXbD @ Design Thinking 2021

Human Centered AI

This is the deck for the Design Thinking 2021 conference, which was held in Austin, TX, last September. This onsite session focused on Human Centered Artificial Intelligence, HC AI.

Quality eXperiences by Design, QXbD, is an interdisciplinary product and service definition practice optimizing for signature value creation.

Relevant disciplines:

  • Human Centered Design, HCD
  • Human Factors Engineering, HFE
  • Human Systems Integration, HSI
  • Human in the Loop Computing, HITL

Source post with additional insights @ innovarista.org – Driving AI with QXbD, Quality eXperiences by Design @ Design Thinking 2021.