Artificial intelligence (AI) is an umbrella term covering a number of technologies, including machine learning (ML), cognitive computing, and natural language processing (NLP). Eric Siegel (@predictanalytic), a former computer science professor at Columbia University, writes, “A.I. is a big fat lie. Artificial intelligence is a fraudulent hoax — or in the best cases it’s a hyped-up buzzword that confuses and deceives.”[1] On the other hand, he notes, “The much better, precise term would instead usually be machine learning — which is genuinely powerful and everyone oughta be excited about it.” Some analysts prefer the term “cognitive technologies” because it better connotes that a number of technologies and methods huddle under the AI umbrella. Several years ago, IBM coined a new term — cognitive computing — which the company believes better describes how cutting-edge techniques can be used to augment human decision-making. Some experts, including Siegel, have problems with the modifier “cognitive” believing it still conjures up images of consciousness. Siegel explains, “The term ‘cognitive computing’ … is another poorly-defined term coined to allege a relationship between technology and human cognition.” Regardless of its imprecision, the term artificial intelligence has proved resilient and isn’t going away. Below are some of the emerging trends experts have identified in the field of AI.
Artificial Intelligence Trends
AI Investments Will Continue to Increase. AI expert Glenn Gow (@glenngow1) reports, “According to ResearchAndMarkets.com, the global artificial intelligence market is expected to grow from $40 billion in 2020 to $51 billion in 2021 at a compound annual growth rate (CAGR) of 28%. The market is expected to reach $171 billion in 2025 at a CAGR of 35%.”[2] He adds, “The companies that have fully embraced AI are focused primarily on: Creating better customer experiences; improving decision-making; and, and innovating on products and services.”
Data Will Dominate AI Discussions. Without data there is no artificial intelligence. Without quality data, there are few beneficial results. Yashar Behzadi (@YasharBehzadi), CEO and Founder of Synthesis AI, observes, “The discussions around data for AI have started, but they haven’t nearly received enough attention. Data is the most critical aspect for building AI systems, and we are just now starting to talk and think about the systems to acquire, prepare, and monitor data to ensure performance and lack of bias. Organizations will have to prioritize a data-first approach within an enterprise architecture in 2022 to enable AI and analytics to solve problems and facilitate new revenue streams.”[3] In 2022, Tate Cantrell (@tate8tech), CTO at Verne Global, predicts, “AI and machine learning models [will] draw on even greater data sets to make increasingly accurate decisions.”[4]
Natural Language Processing Gets More Sophisticated. Cantrell reports, “The latest model of [OpenAI’s large-scale generative pre-trained transformer (GPT)], GPT3, is 100 times the size of its predecessor, with 175bn parameters, making it capable of writing articles that are considered indistinguishable from those written by humans. There’s no doubt that this represents a massive leap forward and has the power to recalibrate how tasks are divided between humans and machines.” These improvements in natural language processing should help companies enhance their customer service through the use of chatbots. The editorial team at Analytics Insight note, “Cognitive computing allows chatbots to have certain level of intelligence about human communication. They understands the users’ needs based on past communication, suggestions, and more and react accordingly.”[5] Rachel Roumeliotis (@rroumeliotis), Vice President of AI and Data at O’Reilly Media, adds, “Artificial intelligence is now powering conversational commerce in retail, increasingly using chatbots to streamline and improve customer service. This can help with everything from answering customer queries and resolving issues to helping sell more merchandise through product recommendations. Voice-to-text translation is a crucial part of this understanding between humans and machines, and it’s getting more sophisticated by the day.”[6]
Companies Embracing AI Will Gain a Significant Advantage. Gow notes, “AI is enabling companies to respond much more quickly to market and operational changes, giving AI-enabled companies a significant advantage.” He adds, “Most companies engage in an annual scenario/strategic planning process. AI can make the strategic planning process an ongoing one. By creating AI models, the strategic plan can be continually updated based on changes in supply, demand, operations, competitive moves, and more. AI can help sense new threats and opportunities and help a company move away from historical reporting to insightful forecasting.” This is exactly what we had in mind when we created the Enterra Global Insights and Decision Superiority System™, a system that leverages Autonomous Decision Science™ (ADS™). ADS combines mathematical computation with semantic reasoning and symbolic logic. The Enterra ADS® platform analyzes data, automatically generates insights, makes decisions with subtlety of judgment like an expert would, and executes those decisions at machine speed with machine reliability.
AI Will Spur Advances in Pure Science. Although some critics have been disappointed with the pace AI has advanced pure science, Cantrell notes, “Advancements in pure mathematics often require inspiration in the form of recognizing a new pattern. And where patterns are the target, artificial intelligence is a terrific tool for the task.” DeepMind recently reported the first two conjectures “in pure mathematics (or math not directly linked to any non-math application) generated by artificial intelligence.”[7]
Risk Assessment and Cybersecurity. AI can be used for both good and nefarious purposes. Adrien Gendre (@gendreadrien), Chief Solution Architect at Vade, says, “Expect cybercriminals to leverage AI-generated email threats especially in targeted attacks. We are currently seeing threats being created manually, but with improved technologies available to mass-produce messaging for email threats based on what’s trending in the news or what is being mentioned in a company’s social accounts, the potential to target their victims is even greater. This could be a game-changer in the way attacks are being built and would put having an AI Response as a must-have in your cybersecurity toolbox.”[8] The Analytics Insight team writes, “Cognitive computing helps combine behavioral data and market trends to generate [risk] insights. Implementing only big data analytics is not enough, enhancing the intelligence of the algorithms using cognitive computing proves effective in risk assessment. … Fraud detection is another application of cognitive computing in finance. It is a type of anomaly detection. Different data analysis techniques like logistic regression, clustering, and more can be used to detect these anomalies.”
Concluding Thoughts
Gow concludes, “The strategic importance of AI is growing at an accelerating pace. Many companies are reaping the rewards of AI now and will increase their investments as a result.” Journalist Jelani Harper predicts, “2022 will usher in a surplus of use cases in which converging AI’s respective connectionist and reasoning approaches, as well as the array of learning methodologies between supervised and unsupervised learning, renders the efficiency and scope of these technologies transformational for everyday business needs.”[9] The AI genie is obviously out of the bottle and companies that master that genie are likely to see their wishes come true.
Footnotes
[1] Eric Siegel, “Why A.I. is a big fat lie,” Big Think, 23 January 2019.
[2] Glenn Gow, “The Top Five Trends In AI: How To Prepare For AI Success,” Forbes, 12 September 2021.
[3] Joyce Wells and Stephanie Simone, “Technology Leaders Share 10 AI Predictions for 2022,” Database Trends and Applications, 6 December 2021.
[4] Jenny Darmody, “5 AI and machine learning trends to watch in 2022,” Silicon Republic, 14 December 2021.
[5] Staff, “Trends of Cognitive Computing Organizations Need to Know Before 2022,” Analytics Insight, 12 December 2021.
[6] Rachel Roumeliotis, “The Future of AI: Assistance with Voice-to-Text Translation,” Dataversity, 16 August 2021.
[7] Stephanie Pappas, “DeepMind cracks ‘knot’ conjecture that bedeviled mathematicians for decades,” Live Science, 6 December 2021.
[8] Wells and Simone, op. cit.
[9] Jelani Harper, “2022 Trends in Artificial Intelligence and Machine Learning: Reasoning Meets Learning,” insideBIGDATA, 5 November 2021.
