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Writer's pictureJohn C. Reynolds, PhD

AI Fundamentals: A Beginner's Guide to Artificial Intelligence

Updated: Oct 18

This article is the first installment of a series titled "Leading in The Algorithmic Revolution: The Impact of Artificial Intelligence on Leadership"


Summary

The 4th industrial revolution (4IR) is a term used to describe the explosion of digital transformation of organizations leveraging the rapid evolution of technology and information management for their success in the 21st Century. A prominent aspect of the 4IR has been the growing significance of the  “algorithmic revolution.” Algorithms are now ubiquitous in commerce, utilized consumer recommendation systems (think Netflix), personalized advertising, fraud detection (think your credit card alerts), predictive analytics (Amazon), and automation of processes (Scan and Go), that were once specialized areas left best to the “geeks” in the business intelligence department. Artificial Intelligence (AI), an outcome of the algorithmic revolution, is rapidly leading to even significant changes in how organizations operate today and in the future, how individuals will become more comfortable in interacting with technology, and how society will continue to integrate AI and its power. For leaders, these advances have resulted in more efficient and accurate decision-making,  process efficiencies, and in some cases the development of innovative products and services (“Hey Google,” Alexis, Siri, personalized movie and book recommendations, to name a few.) However, the algorithmic revolution has also identified challenges related to ethics, transparency, facts, bias, and privacy. The impact of algorithms, specifically AI, on social, economic, and political systems is a subject of ongoing debate and exploration, as it influences the way information is accessed, decisions are made, and information becomes more powerful in individual’s lives. Leaders will be adapted by balancing logical leadership through systems and information with human-centric skills like humility, trust, and transparency. Leading in the algorithmic world will be different and evolving, forcing leaders to be intuitive, discerning, innovative, and sensitive to the humanity of who they are called to lead.


Introduction

In 2019, two Swedish companies (telecommunication and IT) announced the formation of a new Scandinavian technology company, Tieto. Tieto became the first European company to name an AI bot to the leadership team of a new data-oriented business unit. Named Alicia T., the bot can participate in team meetings and vote on business decisions. In Japan, advertising agency McCann named AI-CD, a logic-based system, as creative director. It gave him actual client accounts and campaigns to lead and was preferred in most cases to the human content. The Hong Kong life sciences fund, Deep Knowledge Ventures, appointed a computer algorithm to its board of directors, giving the program a vote on which start-ups to invest in. What is intriguing is that these events occurred in 2019, 2014, and 2016, respectively. The recent popularity and availability of open-source ChatGPT and similar products have highlighted the ease and growing popularity of AI in society and the workplace. It's estimated that ChatGPT hit 100 million monthly active users in January 2023 (60 days), making it the fastest-growing application in history. To put that into perspective, TikTok took 9 months to reach 100 million users, and Instagram took 2.5 years. The age of the algorithmic revolution is here, the impact of artificial intelligence in the global economy is exploding, the workforce is still reviving after the pandemic, so what should leaders be considering as they lead and adapt to these uncharted times?


A bar chart displaying how long it took each social media platform to reach 1 million users

What is the Algorithmic Revolution?

The algorithmic revolution generally refers to the transformative impact of algorithms on various aspects of society, particularly in the realm of technology and data-driven decision-making or digital transformation. The concept describes the rapid advancement and adoption of algorithms, defined as step-by-step procedures or sets of rules, for solving problems or accomplishing tasks. We experience the impact of this revolution every day through retail solicitation by email or messaging that almost seems to “read our minds.” The algorithmic revolution has been accelerated in the last several years through exponential advancements in the speed of computing power, seemingly unlimited data storage and its manipulation, executed through complex and sophisticated computations, data analysis, and pattern recognition with processing costs that now make this advancement economically viable.


What is Artificial Intelligence?

AI may be regarded as the beginning of business use in what is considered the algorithmic revolution. Historically there were two competing approaches in the evolution of AI. The most popular approach for almost 60 years in AI has been the logic-based approach (think Algebra). This approach is generally referred to as ‘good old-fashioned artificial intelligence’ or  “GOFAI”. The second approach was driven by ‘artificial neural networks’ loosely inspired by how our brains work or human biology (neural pathways).


A visual timeline of the development and rise of artificial intelligence

In the late 20th century, GOFAI was the more successful approach resulting in large research projects and significant government funding; however, resulting in little impact or pragmatic application. Artificial neural networks also struggled, and by the 1990s, AI research had mostly disappeared from public, government, and industrial interest/funding. 


In November 2022, this all changed when ChatGPT, an open-source AI chatbot, became accessible in the public domain enabling the general public to create conversational dialogue simulating human interaction with technology. This latest surge of interest and development is a result of the increasing power of deep learning, a type of biologically-inspired neural network that is beginning to optimize the huge “lakes” of data now available, and the massive computational power and speed of today’s computer technology.


With enormous data sets now being captured and accessible, modern AI neural networks can often exceed human performance in many tasks previously very difficult for AI. In addition, unlike GOFAI, today’s AI systems are “learning” from experience, and unlike GOFAI, reason heuristically - something that humans do naturally, generally learning from a single experience. However, this advancement has received a mixed welcome to the global economy. In April 2023, Italy temporarily banned ChatGPT and has been joined by other lawmakers and governments in debating laws, with a long horizon to how these may be enforced. An interesting response when considering that facial recognition, an AI-driven technology, is being used by millions on smartphones and for travel. The crux of the issue in government and corporate response appears to be the fear of the inability of the workforce to adapt and perhaps even replace the workforce as we know it today. Rapidly advancing technology, a skittish workforce recovering from a pandemic, global uncertainty, rumors of an economic recession, historically high inflation - how does one lead and lead well in time such as these?  The immediate need is for leaders to develop a new set of skills and competencies to effectively navigate the complex interplay between algorithms, employees, and organizational goals. By understanding and embracing the algorithmic revolution, leaders can adapt and leverage its huge potential to drive innovation, enhance decision-making processes, and foster a culture of agility and adaptability within their organizations. Before considering the impact on leaders, a quick review of the positive characteristics that are often associated with the algorithmic revolution and its impact in the organization.


A satyrical version of a Time Magazine cover showing a Robot in a suit with the headline "Best CEO in History"

[Continued in Part 2]

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