From our attitude towards work to our grasp of what two metres look like, the coronavirus pandemic has made us rethink how we see the world. But while we've found it hard to adjust to the new reality, it's been even harder for the narrowly-designed artificial intelligence models that have been created to help organisation make decisions. Based on data that described the world before the crisis, these won't be making correct predictions anymore, pointing to a fundamental problem in they way AI is being designed.
David Cox, IBM director of the MIT-IBM Watson AI Lab, explains that faulty AI is particularly problematic in the case of so-called black box predictive models: those algorithms which work in ways that are not visible, or understandable, to the user. "It's very dangerous," Cox says, "if you don't understand what's going on internally within a model in which you shovel data on one end to get a result on the other end. The model is supposed to embody the structure of the world, but there is no guarantee that it will keep working if the world changes."
The COVID-19 crisis, according to Cox, has only once more highlighted what AI experts have argued for decades: that algorithms should be more explainable.
SEE: How to implement AI and machine learning (ZDNet special report) | Download the report as a PDF (TechRepublic)
For example, if you were building a computer program that was a complete blackbox, aimed at predicting what the stock market would be like based on past data, there is no guarantee it's going to continue to produce good predictions in the current coronavirus crisis, he argues.
What you actually need to do is build a broader model of the economy that acknowledges supply and demand, understands supply-chains, and incorporates that knowledge, which is closer to something that an economist would do. Then you can reason about the situation more transparently, he says.
"Part of the reason why those models are hard to trust with narrow AIs is because they don't have that structure. If they did it would be much easier for a model to provide an explanation for why they are making decisions. These models are experiencing challenges now. COVID-19 has just made it very clear why that structure is important," he warns.
It's important not only because the technology would perform better and gain in reliability, but also because businesses would be far less reluctant to adopt AI if they trusted the tool more. Cox pulls out his own statistics on the matter: while 95% of companies believe that AI is key to their competitive advantage, only 5% say they've extensively implemented the technology.
While the numbers differ from survey to survey,the conclusion has been the same for some time now: there remains a significant gap between the promise of AI and its reality for businesses. And part of the reason that industry is struggling to deploy the technology boils down to a lack of understanding of AI. If you build a great algorithm but can't explain how it works, you can't expect workers to incorporate the new tool in their business flow. "If people don't understand or trust those tools, it's going to be a lost cause," says Cox.
Explaining AI is one of the main focuses of Cox's work. The MIT-IBM Watson Lab, which he co-directs, comprises of 100 AI scientists across the US university and IBM Research, and is now in its third year of operation. The Lab's motto, which comes up first thing on its website, is self-explanatory: "AI science for real-world impact".
Back in 2017, IBM announced a $240 million investment over ten years to support research by the firm's own researchers, as well as MIT's, in the newly-founded Watson AI Lab. From the start, the collaboration's goal has had a strong industry focus, with an idea to unlock the potential of AI for "business and society". The lab's focus is not on "narrow AI", which is the technology in its limited format that most organizations know today; instead the researchers should be striving for "broad AI". Broad AI can learn efficiently and flexibly, across multiple tasks and data streams, and ultimately has huge potential for businesses. "Broad AI is next," is the Lab's promise.
The only way to achieve broad AI, explains Cox, is to bridge between research and industry. The reason that AI, like many innovations, remains stubbornly stuck in the lab, is because the academics behind the technology struggle to identify and respond to the real-world needs of businesses. Incentives are misaligned; the result is that organizations see the potential of the tool, but struggle to use it. AI exists and it is effective, but is still not designed for business.
SEE: Developers say Google's Go is 'most sought after' programming language of 2020
Before he joined IBM, Cox spent ten years as a professor in Harvard University. "Coming from academia and now working for IBM, my perspective on what's important has completely changed," says the researcher. "It has given me a much clearer picture of what's missing."
The partnership between IBM and MIT is a big shift from the traditional way that academia functions. "I'd rather be there in the trenches, developing those technologies directly with the academics, so that we can immediately take it back home and integrate it into our products," says Cox. "It dramatically accelerates the process of getting innovation into businesses."
IBM has now expanded the collaboration to some of its customers through a member program, which means that researchers in the Lab benefit from the input of players from different industries. From Samsung Electronics to Boston Scientific through banking company Wells Fargo, companies in various fields and locations can explain their needs and the challenges they encounter to the academics working in the AI Watson Lab. In turn, the members can take the intellectual property generated in the Lab and run with it even before it becomes an IBM product.
Cox is adamant, however, that the MIT-IBM Watson AI Lab was also built with blue-sky research compatibility in mind. The researchers in the lab are working on fundamental, cross-industry problems that need to be solved in order to make AI more applicable. "Our job isn't to solve customer problems," says Cox. "That's not the right use for the tool that is MIT. There are brilliant people in MIT that can have a hugely disruptive impact with their ideas, and we want to use that to resolve questions like: why is it that AI is so hard to use or impact in business?"
Explainability of AI is only one area of focus. But there is also AutoAI, for example, which consists of using AI to build AI models, and would let business leaders engage with the technology without having to hire expensive, highly-skilled engineers and software developers. Then, there is also the issue of data labeling: according to Cox, up to 90% of the data science project consists of meticulously collecting, labeling and curating the data. "Only 10% of the effort is the fancy machine-learning stuff," he says. "That's insane. It's a huge inhibitor to people using AI, let alone to benefiting from it."
SEE: AI and the coronavirus fight: How artificial intelligence is taking on COVID-19
Doing more with less data, in fact, was one of the key features of the Lab's latest research project, dubbed Clevrer, in which an algorithm can recognize objects and reason about their behaviors in physical events from videos. This model is a neuro-symbolic one, meaning that the AI can learn unsupervised, by looking at content and pairing it with questions and answers; ultimately, it requires far less training data and manual annotation.
All of these issues have been encountered one way or another not only by IBM, but by the companies that signed up to the Lab's member program. "Those problems just appear again and again," says Cox and that's whether you are operating in electronics or med-tech or banking. Hearing similar feedback from all areas of business only emboldened the Lab's researchers to double down on the problems that mattered.
The Lab has about 50 projects running at any given time, carefully selected every year by both MIT and IBM on the basis that they should be both intellectually interesting, and effectively tackling the problem of broad AI. Cox maintains that within this portfolio, some ideas are very ambitious and can even border blue-sky research; they are balanced, on the other hand, with other projects that are more likely to provide near-term value.
Although more prosaic than the idea of preserving purely blue-sky research, putting industry and academia in the same boat might indeed be the most pragmatic solution in accelerating the adoption of innovation and making sure AI delivers on its promise.
See the article here:
- Artificial Intelligence (AI) Definition - Investopedia - May 31st, 2020
- The Temptations Of Artificial Intelligence Technology And The Price Of Admission - Forbes - May 31st, 2020
- Artificial intelligence offers a chance to optimize COVID-19 treatment in international partnership - Vanderbilt University News - May 31st, 2020
- Reality Check: The Benefits of Artificial Intelligence - AiThority - May 31st, 2020
- Thanks To Renewables And Machine Learning, Google Now Forecasts The Wind - Forbes - May 31st, 2020
- Artificial intelligence is hopelessly biased - and that's how it will stay - TechRadar India - May 31st, 2020
- Top Artificial Intelligence Trends that will Change the Decade - Analytics Insight - May 31st, 2020
- Art and artifice - The Indian Express - May 31st, 2020
- The Role of Artificial Intelligence in Ethical Hacking | EC-Council Official Blog - EC-Council Blog - May 31st, 2020
- Microsoft is cutting dozens of MSN news production workers and replacing them with artificial intelligence - Seattle Times - May 31st, 2020
- Artificial intelligence software improves accuracy, doubles speed in evaluating CT scans of advanced cancer - UAB News - May 31st, 2020
- Coronavirus tests the value of artificial intelligence in medicine - FierceHealthcare - May 31st, 2020
- The Use of Artificial Intelligence by Investment Advisers: Considerations Based on an Advisers Fiduciary Duties - JD Supra - May 31st, 2020
- Lecturer in Artificial Intelligence for Digital Infrastructures job with UNIVERSITY OF BRISTOL | 208485 - Times Higher Education (THE) - May 31st, 2020
- Artificial Intelligence (AI) Market to Reach USD 202.57 Billion by 2026; Rising Demand for Cloud-based Applications to Aid Growth: Fortune Business... - May 31st, 2020
- Walmart Employees Are Out to Show Its Anti-Shoplifting AI Doesn't Work - WIRED - May 31st, 2020
- How artificial intelligence is keeping time-critical shipments on track during pandemic - FreightWaves - May 31st, 2020
- Coronavirus Update: Recent FTC Guidance on the Use of Artificial Intelligence and Algorithms in the Age of COVID-19 - Government Contracts Legal Forum - May 31st, 2020
- COVID-19 Impact: A Mix of Challenges and Opportunities | Artificial Intelligence-as-a-Service (AIaaS) Market 2020-2024 | Growing Adoption of Cloud... - May 31st, 2020
- IIT-Ropar and TSW Launch a PG Programme in Artificial Intelligence - THE WEEK - May 31st, 2020
- MS in Artificial Intelligence | Artificial Intelligence - May 19th, 2020
- What is Artificial Intelligence? | Azure Blog and Updates ... - May 19th, 2020
- What Are the Advantages of Artificial Intelligence ... - May 19th, 2020
- AI Tutorial | Artificial Intelligence Tutorial - Javatpoint - May 19th, 2020
- It's Called Artificial Intelligencebut What Is Intelligence? - WIRED - May 19th, 2020
- Powering the Artificial Intelligence Revolution - HPCwire - May 19th, 2020
- An AI future set to take over post-Covid world - The Indian Express - May 19th, 2020
- A New Way To Think About Artificial Intelligence With This ETF - MarketWatch - May 19th, 2020
- Artificial intelligence-based imaging reconstruction may lead to incorrect diagnoses, experts caution - Radiology Business - May 19th, 2020
- Artificial Intelligence in the Covid Frontline - Morningstar - May 19th, 2020
- Patent Analytics Market to Reach USD 1,668.4 Million by 2027; Integration of Machine Learning and Artificial Intelligence to Spur Business... - May 19th, 2020
- Artificial Intelligence in Cancer: How Is It Used in Practice? - Cancer Therapy Advisor - May 19th, 2020
- Five Important Subsets of Artificial Intelligence - Analytics Insight - May 19th, 2020
- Ethical artificial intelligence: Could Switzerland take the lead? - swissinfo.ch - May 19th, 2020
- The Future of Artificial Intelligence: Edge Intelligence - Analytics Insight - May 19th, 2020
- 5 Ways Artificial Intelligence Is Changing Architecture - May 15th, 2020
- Keysight Validates Artificial Intelligence (AI) and ... - May 15th, 2020
- What Is Artificial Intelligence? Examples and News in 2019 ... - May 15th, 2020
- Artificial Intelligence (AI) Is Nothing Without Humans - E3zine.com - May 15th, 2020
- Artificial intelligence is helping seniors who are isolated during the coronavirus pandemic - WXYZ - May 15th, 2020
- ValleyML is launching a Machine Learning and Deep Learning Boot Camp from July 14th to Sept 10th and AI Expo Series from Sept 21st to Nov 19th 2020.... - May 15th, 2020
- TSA Issues Road Map to Tackle Insider Threat With Artificial Intelligence - Nextgov - May 15th, 2020
- The Expanding Role Of Artificial Intelligence In Tax - Forbes - May 15th, 2020
- Artificial Intelligence: Technology Of The Future - Forbes India - May 15th, 2020
- SparkCognition and Milize to Offer Automated Machine Learning Solutions for Financial Institutions to the APAC Region - PRNewswire - May 15th, 2020
- Alpha Modus Allowed 2nd Patent Leveraging Artificial Intelligence for Monitoring and Analyzing Consumer Behavior - Yahoo Finance - May 15th, 2020
- Tesla : Artificial Intelligence - the .AI domain is on the rise - marketscreener.com - May 15th, 2020
- Artificial Intelligence Can Only Help Architecture if We Ask the Right Questions - ArchDaily - May 15th, 2020
- Fighting COVID-19: Artificial Intelligence community to help citizens and the healthcare system - Canada NewsWire - May 15th, 2020
- Understanding the Four Types of Artificial Intelligence - May 9th, 2020
- Artificial intelligence Facts for Kids - May 9th, 2020
- 4 Main Types of Artificial Intelligence - G2 - May 9th, 2020
- Artificial intelligence project lets Holocaust survivors ... - May 9th, 2020
- Artificial intelligence - Simple English Wikipedia, the ... - May 9th, 2020
- Artificial Intelligence Market by Size, Share, Analysis ... - May 9th, 2020
- A.I. Artificial Intelligence movie review (2001) | Roger Ebert - May 9th, 2020
- Artificial Intelligence is Evolving to Process the World Like Humans - Interesting Engineering - May 9th, 2020
- Drug research turns to artificial intelligence in COVID-19 fight - Business in Vancouver - May 9th, 2020
- Women wanted: Why now could be a good time for women to pursue a career in AI - CNBC - May 9th, 2020
- Artificial Intelligence Used to Identify Light Sources With Far Fewer Measurements - Unite.AI - May 9th, 2020
- The Impending Artificial Intelligence Revolution in Healthcare - Op-Ed - HIT Consultant - May 9th, 2020
- COVID-19 identification in X-ray images by Artificial intelligence - News Anyway - May 9th, 2020
- Is artificial intelligence the answer to the care sector amid COVID-19? - Descrier - May 9th, 2020
- Artificial intelligence - Wikipedia - April 26th, 2020
- artificial intelligence | Definition, Examples, and ... - April 26th, 2020
- What Is Artificial Intelligence (AI)? | PCMag - April 26th, 2020
- How Artificial Intelligence Is Totally Changing Everything ... - April 26th, 2020
- Artificial Intelligence And Automation Top Focus For Venture Capitalists - Forbes - April 26th, 2020
- Benefits & Risks of Artificial Intelligence - Future of ... - April 26th, 2020
- Artificial intelligence can take banks to the next level - TechRepublic - April 26th, 2020
- Health care of tomorrow, today: How artificial intelligence is fighting the current, and future, COVID-19 pandemic | TheHill - The Hill - April 26th, 2020
- How Artificial Intelligence, IoT And Big Data Can Save The Bees - Forbes - April 26th, 2020
- First meeting of the new CEPEJ Working Group on cyberjustice and artificial intelligence - Council of Europe - April 26th, 2020
- When the coronavirus hit, California turned to artificial intelligence to help map the spread - 60 Minutes - CBS News - April 26th, 2020
- Artificial Intelligence in the Oil & Gas Industry, 2020-2025 - Upstream Operations to Witness Significant Growth - ResearchAndMarkets.com - Yahoo... - April 26th, 2020
- Pre & Post COVID-19 Market Estimates-Artificial Intelligence (AI) Market in Retail Sector 2019-2023| Increased Efficiency of Operations to Boost... - April 26th, 2020
- EUREKA Clusters Artificial Intelligence (AI) Call | News item - The Netherlands and You - April 26th, 2020
- A guide to healthy skepticism of artificial intelligence and coronavirus - Brookings Institution - April 2nd, 2020
- AI vs your career? What artificial intelligence will really do to the future of work - ZDNet - April 2nd, 2020
- Return On Artificial Intelligence: The Challenge And The Opportunity - Forbes - April 2nd, 2020