Of the 30 emerging technologies featured in Gartner’s latest Hype Cycle, nine are directly related to artificial intelligence:

• Generative adversarial networks
• Adaptive machine learning
• Composite AI
• Generative AI
• Responsible AI
• AI-augmented development
• Embedded AI
• Trusted AI
• AI-augmented design

Most of the AI technologies are currently in the initial “Innovation Trigger” part of the Hype Cycle, where excitement builds the fastest.

Responsible AI, AI-augmented development, embedded AI, and Trusted AI, have all now reached the “Peak of Inflated Expectations” and will next move into the dreaded “Trough of Disillusionment” as disappointment sets in over what can realistically be achieved.

Only after the trough, which none of the AI technologies have yet reached, do we head into the areas of the Hype Cycle where adoption occurs with realistic expectations and the productivity rewards are reaped.

Gartner’s Hype Cycle covers the next decade. The current placings of most of the AI technologies on the Hype Cycle indicates that Gartner believes it won’t be until towards the end of the decade we’ll see the most benefits.

Brian Burke, VP of research at Gartner, comments:

“Emerging technologies are disruptive by nature, but the competitive advantage they provide is not yet well known or proven in the market. Most will take more than five years, and some more than 10 years, to reach the Plateau of Productivity.

But some technologies on the Hype Cycle will mature in the near term and technology innovation leaders must understand the opportunities for these technologies, particularly those with transformational or high impact.”

Two technologies which Gartner expects to fast-track through the Hype Cycle are health passports and social distancing technologies, due to their necessity amid the COVID-19 pandemic.

You can find the full Gartner report here (paywall)

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Musk has been among the most vocal prominent figures in warning about the dangers of artificial intelligence. In 2018, for example, Musk famously warned that AI could become “an immortal dictator from which we would never escape” and that the technology is more dangerous than nuclear weapons.

Speaking in a New York Times interview, Musk said that current trends suggest AI could overtake humans by 2025. However, Musk adds “that doesn’t mean that everything goes to hell in five years. It just means that things get unstable or weird.”

If correct, the latest prediction from Musk would mean the so-called technological singularity – when machine intelligence overtakes human – is set to happen much sooner than other experts predict. Ray Kurzweil, a respected futurist, has previously estimated the aforementioned singularity to occur around 2045.

As the founder of Tesla, SpaceX, and Neuralink – three companies which use AI far more than most – Musk isn’t against the technology, but has called for it to be regulated.

Musk also founded OpenAI back in 2015 with the goal of researching and promoting ethical artificial intelligence. Following disagreements with the company’s direction, Musk left OpenAI in 2018.

Back in February, Musk responded to an MIT Technology Review profile of OpenAI saying that it “should be more open” and that all organisations “developing advanced AI should be regulated, including Tesla.”

Last year, OpenAI decided not to release a text generator which it believed to have dangerous implications in a world already struggling with fake news and disinformation campaigns.

Two graduates later recreated and released a similar generator to OpenAI’s, with one saying that it “allows everyone to have an important conversation about security, and researchers to help secure against future potential abuses.”

OpenAI has since provided select researchers access to their powerful text generator. The latest version, GPT-3, has been making headlines in recent weeks for the incredible things it can achieve with limited input.

GPT-3 offers 175 billion parameters compared to GTP-2’s 1.5 billion parameters – which shows the rapid pace of AI advancements. However, Musk’s prediction of the singularity happening within five years perhaps needs to be taken with a pinch of salt.

(Image Credit: Elon Musk by JD Lasica under CC BY 2.0 license)

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AI is proving itself to be an important tool in tackling some of the biggest issues the world faces today; including coronavirus and climate change. However, some public distrust remains.

“The current pandemic has shown us more needs to be done to speed up the adoption of trusted AI around the world,” said Kay Firth-Butterfield, Head of Artificial Intelligence and Machine Learning at the World Economic Forum.

“We moved from guidelines to practical tools, tested and iterated them – but this is still just a start. Now we will be working to scale them to countries around the world.”

The guidelines released today aim to “help society tackle big data problems faster” while also preparing them for future risks. The UK government adopted the guidelines across its various departments.

“The UK is a global leader in AI and I am pleased we are working with the World Economic Forum and international partners to develop guidelines to ensure its safe and ethical deployment,” said Caroline Dinenage, Digital Minister of the United Kingdom.

“By taking a dynamic approach we can boost innovation, create competitive markets and support public trust in artificial intelligence. I urge public sector organisations around the world to adopt these guidelines and consider carefully how they procure and deploy these technologies.”

For the past year, the WEF has worked alongside the UK’s Office for AI; companies such as Deloitte, Salesforce, and Splunk; 15 other countries; and more than 150 members of government, academia, civil society, and the private sector.

“As a trusted AI advisor to governments around the world, we were thrilled to collaborate with the World Economic Forum and the government of the UK in the development of procurement guidelines that help the public sector put AI at the service of its constituents in a manner that is both efficient and ethical,” said Shelby Austin, Managing Partner, Growth & Investments and Omnia AI, Deloitte, Canada.

“As our societies reorganize and make progress in our fight against COVID-19, the need for multi-stakeholder cooperation has never been more apparent. We believe in these joint efforts, and we believe in the power of data-driven decision-making to help our countries recover and thrive.”

The result of the joint effort was the “Procurement in a Box” toolkit which provides guidance from conducting drafting proposals and conducting risk assessments, all the way to purchasing AI solutions and deploying them in a trusted manner.

A proposal for a chatbot allowing executives for the Dubai Electricity and Water Authority (DEWA) to obtain answers to data-related questions was used to test the guidelines. DEWA’s chatbot was successful and serves as an early example of how rapid but safe AI deployments can be achieved using the guidelines.

“In an era that will continue to be dominated by the transformative technologies emerging from the Fourth Industrial Revolution, integrating AI into the public sector for everyday use will significantly elevate the performance of government departments,” said Khalfan Belhoul, CEO of the Dubai Future Foundation, the host entity of Centre for the Fourth Industrial Revolution UAE.

You can find a copy of the Procurement in a Box toolkit here (PDF)

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Edison is an AI platform launched last year to help with leveraging data from imaging devices.

Kieran Murphy, President and CEO at GE Healthcare, says:

“We introduced Edison just one year ago at RSNA to help health providers take advantage of data in new and significant ways.

With the introduction of the Edison Developer Program, and a suite of new intelligent applications and smart devices powered by Edison, we are building on that promise as we continue to work with partners to realize our collective goal of advancing the future of health.”

While there’s significant interest in using AI for healthcare, the time it takes for implementing new innovations is “cumbersome and complex,” according to GE Healthcare.

GE Healthcare aims to serve clinicians’ need for a single solution to assist with integrating AI algorithms into existing workflows to help them, and therefore their patients, benefit from the potential of these new technologies much faster.

Market-ready AI applications will be deeply integrated into GE Healthcare’s vast existing solutions – on medical devices, in the cloud, or at the edge of the network.

Developers jumping aboard the new initiative will have the reach of GE Healthcare’s large userbase. GE Healthcare’s business reported $19 billion in revenue last year and spans 160 countries. On average, three patients are imaged with the company’s solutions every second.

“The Edison Developer Program exposes a number of potential capabilities of the Edison platform, including secure device connectivity, data aggregation for clinical context, advanced visualization, workflow and AI orchestration, in addition to a rich set of AI capabilities for data traceability, curation, annotation, model training and inferencing,” the company wrote in a press release.

“This set of services will reduce the complexity of developing and integrating AI and data-based healthcare applications in clinical workflows. Program members are selected and vetted based on rigorous clinical and technical evaluations as well as regulatory clearance to ensure confidence and security of solutions offered through the Edison platform.”

GE Healthcare is currently working with a range of AI and analytics companies including Arterys, iCAD, Koios Medical, MaxQ AI and Volpara.

Koios Medical, for example, built and deployed Breast Assistant – an AI-based risk assessment for breast cancer that aligns to a BI-RADS (Breast Imaging-Reporting and Data System) category.

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According to figures published by ABI Research, the United States received 52.3 percent of global AI investments in 2018.

In 2018, investments in US-based AI technologies reached a total of $9.7 billion. This represents a staggering 120 percent year-on-year growth.

Huge AI investments from companies such as Zoox, Cruise Automation, Zymergen, and Dataminr helped to propel the US back into the number one spot.

The gap between the US and China is only expected to increase based on investment figures this year. ABI Research expects the US to reach a 70 percent share of global AI investments.

Lian Jye Su, Principal Analyst at ABI Research, said: 

“The United States is reaping the rewards from its diversified AI investment strategy. 

Top AI startups in the United States come from various sectors, including self-driving cars, industrial manufacturing, robotics process automation, data analytics, and cybersecurity.

All these startups research on and invest in cutting edge deep learning technologies in their solutions, democratising AI for enterprises and end consumers.”

China also continues to see healthy growth in its AI sector. Year-on-year it’s grown 54 percent to reach a total of $7.4 billion.

Beijing itself has doubled-down on its ambitions to be a world leader in AI. The country’s rollout of the largest commercially-available 5G network in the world today will help to support this endeavour.

China has many established AI leaders, such as SenseTime and CloudWalk. The former is the world’s most funded AI startup and has a valuation of more than $4.5 billion, in part due to its provision of surveillance services to Beijing.

SenseTime’s Viper system aims to process and analyse over 100,000 simultaneous real-time streams from traffic cameras, ATMs, and more to automatically tag and keep track of individuals.

ABI Research predicts China will continue to witness growth but will suffer from “strong headwinds” due to the ongoing trade war with the US. The researchers believe attempts by the Americans to reduce Chinese firms’ access to US tech has slowed AI advancements in China.

“There is no doubt that Chinese AI investment is feeling the pinch of reality, but China is still undeniably the largest single market for AI implementation,” comments Su.

“Favourable policies and flexible regulations in China, backed by a government willing to invest and deploy innovative technologies at scale, will certainly amplify AI adoption in the region.”

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The use of AI to increase productivity rather than replace human workers will help to quell some fears around the adoption of artificial intelligence.

Svetlana Sicular, Research Vice President at Gartner, said:

“Augmented intelligence is all about people taking advantage of AI.

As AI technology evolves, the combined human and AI capabilities that augmented intelligence allows will deliver the greatest benefits to enterprises.”

Gartner is predicting the adoption of AI will generate $2.9 trillion in business value in 2021. Furthermore, it will deliver the equivalent of 6.2 billion hours of worker productivity over the same timeframe.

Currently, the leading business value of AI is decision support/augmentation, followed by agents. By 2030, Gartner predicts this overall ranking will remain the same but the gap between will grow significantly with decision support/augmentation accounting for 44 percent of business value, and agents representing 24 percent.

“The excitement about AI tools, services and algorithms misses a crucial point: The goal of AI should be to empower humans to be better, smarter and happier, not to create a ‘machine world’ for its own sake,” added Sicular. “Augmented intelligence is a design approach to winning with AI, and it assists machines and people alike to perform at their best.”

Decision support/augmentation will have little impact on the workforce, but that doesn’t mean workers have nothing to fear. Agents, the second biggest expected driver of business value, will inevitably cause some job losses.

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Last week, AI News reported on a Microsoft study which highlighted that high-growth companies are over twice as likely to be using AI. 41 percent of high-growth companies are using AI compared to just 19 percent of low-growth.

This divide needs to change or small businesses risk falling even further behind. However, overall, less than two in 10 of even high-growth companies are integrating AI which presents a huge opportunity.

Microsoft is launching AI Business School which provides lectures, case studies, guides, talks, and resources from industry leaders as well as Microsoft’s own executives. The course is designed to be for people with a business background so it’s non-technical.

“There is a gap between what people want to do and the reality of what is going on in their organisations today, and the reality of whether their organisation is ready,” said Mitra Azizirad, corporate vice president for AI marketing at Microsoft.

“Developing a strategy for AI extends beyond the business issues,” she explained. “It goes all the way to the leadership, behaviours and capabilities required to instill an AI-ready culture in your organisation.”

The new ‘Business School’ is an extension of Microsoft’s existing ‘AI School’ which is a more technical course.

You can find out more about the AI Business School here.

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One standout result of the study is that German, British, Russian, Dutch, Swiss, and Italian business leaders are – on the whole – reporting they’re “actively implementing” AI ahead of the US.

In fact, of business leaders from the countries surveyed, only France was behind the US.

The survey did not include all countries and is missing several notable countries including the likes of Japan, Canada, and Australia. Of course, the biggest omission is China.

China and the US are leaders in AI development but Microsoft’s study indicates that isn’t translating into adoption by American businesses.

Another interesting highlight in Microsoft’s study is the disparity in adoption between high and low growth companies.

High-growth companies, defined as having double-digit growth, are over twice as likely to be using AI. 41 percent of high-growth companies are using AI compared to just 19 percent of low-growth.

This disparity is most prominent in Germany where 67 percent of high-growth companies are using AI compared to just 17 percent of low-growth.

Susan Etlinger, Industry Analyst with the Altimeter Group, said:

“What’s striking about the research is the difference between double-digit growth companies and those with lower growth.

Double-digit growth companies are further along in their AI deployments, but also see a greater urgency in using more AI. They are looking at a one to three year timeframe – often really focused on the coming year. Lower growth companies are looking at more of a 5-year timeframe. What this says to me is that the more you know, the higher your sense of urgency is.”

Most of the businesses are either in the ‘exploring’ or ‘experimenting’ stages on their AI journey. The competitive advantages to using AI are clear, but it’s worth starting small and scaling up deployments over time.

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