Technology

Navigating the Advancement of AI-Based Solutions

Research and development in artificial intelligence (AI) have existed since the early 1950s. However, it was only in the past decade that AI development has truly accelerated, and its applications in the business world exploded across industries. This acceleration was enabled by foundational elements such as unparalleled processing power, unlimited storage capacity, global connectivity, low cost of hardware production, and intuitive interfaces that propelled mass consumer adoption of AI-based solutions.

AI Is Vital to Digital Business Transformation

AI has entered the mainstream business landscape as a necessary component of the digital business transformation road map. In the business world, however, there’s still a great deal of confusion about what AI is and how it contributes to an organization’s digital transformation. I often find myself in discussions with people—experts, industry leaders, and even friends and family—on AI and its potential impact on our lives. Almost everyone has an opinion on the topic—sometimes very strong and polarizing opinions—perhaps due to the popularity of referencing AI in mainstream media. Since the 1920s, Hollywood movies have used AI as their protagonist and often even antagonist, solidifying a mass perception of the technology, its capabilities, and its potential impact on mankind. Movies such as Her, Ex Machina, A.I. Artificial Intelligence, and more recently Mother/Android tell stories of a powerful AI that has the potential to experience consciousness and overpower humans.

AI can be defined as the automation of cognitive processes—the science and engineering of making intelligent machines and using computers to understand human intelligence (referencing the definition by John McCarthy, computer scientist and one of the founders of the discipline of AI). It’s a field that combines computer science with large, reliable data sets to facilitate problem-solving and mimic human intelligence to perform tasks. Machine learning and deep learning are two subfields that are frequently mentioned in the context of AI. These disciplines are made up of AI algorithms that aim to develop expert systems that can make predictions or classifications based on the data they’re fed.

In 2023, mainstream use of generative AI platforms was rapidly adopted due to their ease of use, accessibility, and intuitive nature. AI-based solutions are revolutionizing business functions through smarter decision-making, increased productivity, streamlined operations, and enhanced innovation. These tools are used across multiple sectors, such as health care, entertainment, virtual assistance, predictive maintenance systems, etc. The potential of AI in the business world and our lives is barely tapped into, while machine learning techniques have significantly advanced the capabilities of AI systems in a short amount of time.

Given these technologies have real-world applications and effects, the development of AI has been a topic of great interest and concern among tech leaders and academics and, more recently, mainstream media. A recent open letter signed by Elon Musk and other prominent technology leaders has urged AI developers to cease the training of some of their more sophisticated AI experiments, citing potential risks that could trigger a “loss of control of our civilization.” The open letter, signed by over 1,400 industry leaders, highlights how the advent of neural networks and reinforcement learning algorithms could create AI systems beyond human comprehension or control, which could pose a serious threat to human civilization.

The letter has sparked debates within the tech industry, with some experts claiming such a drastic measure could hamper scientific progress, while others believe AI systems need to have clear ethical and legal frameworks in place before being developed further. Geoffrey Hinton, renowned tech pioneer and “Godfather of AI,” recently expressed regret over the development of AI due to potential misuse. Hinton’s contributions have led to tools such as ChatGPT being used by millions worldwide. Despite the revolutionary impact of his work, Hinton is concerned about the potential implications of unbounded AI, including the easy access to AI text- and image-generation tools that could lead to more fake or fraudulent content being created, making it difficult for the average person to know what’s true and credible. With the increased sophistication of AI systems, there are risks of loss of privacy, security, and jobs, as well as discrimination and bias. As AI-based technologies advance, there’s also a high risk of consolidation of power in the hands of a few organizations or governments, potentially undermining democracy and creating monopolies.

Pausing the Training and Development of AI Systems Is Not the Solution

The solution to call for an “immediate pause for at least 6 months of the training of AI systems” falls short of what’s truly required. The deep-rooted issues in the tech industry are much broader and need to be tackled from various aspects to ensure the transformative impact of innovative technologies is encouraged in a responsible way. International regulatory bodies and intelligent governance for AI development will be crucial through implementing agreements on AI research, development, and deployment, as well as open sharing of adaptable best practices and regulations. This requires ongoing monitoring, evaluation, and public discourse to ensure regulatory frameworks remain relevant and effective in addressing emerging challenges.

In addition, increased collaboration across the industry by building an ecosystem of key stakeholders, including technology companies, industry leaders, corporates, thought leaders, and experts, as well as regulators and end consumers, to ensure a range of people understand and are involved in the development of AI is needed. In addition, we need to establish open and transparent dissemination of information relating to the sources and use of data for AI-based systems.

The ethical responsibility of AI developers is paramount; they must ensure their AI systems adhere to ethical principles such as privacy, transparency, and autonomy. Increasing diversity in development and testing teams for AI-based systems facilitate the diversity of thought that will help avoid groupthink and bias, as well as ensure ethical views are taken into account. Developers should be accountable for any adverse effects of their AI systems, as well as work to prevent existing biases from being perpetuated.

The complexity and ambiguity associated with AI technology call for collaborative solutions that involve diverse stakeholders. As AI continues to penetrate various aspects of society, it becomes increasingly important to ensure all decisions and actions that involve AI are thoroughly informed by research and ethical considerations. It’s essential to understand the ethical implications of AI aren’t limited to technical solutions but instead require a multidisciplinary approach that considers a range of factors, such as collaboration, privacy, responsibility, transparency, and accountability.

Kamales Lardi is a bold and strategic thinker in digital and business transformation. She combines over 23 years of deep cross-industry experience with the latest digital and technology solutions and is listed in the “Top 10 Global Influencers & Thought Leaders in Digital Transformation” (Thinkers360) and Top 50 Women in Tech Influencers 2021 (The Awards Magazine). She often says that “technology is not a silver bullet solution, a clear value proposition should drive any transformation effort.” This approach resonates well with many business leaders and has helped her stand out in the digital space. Since establishing Lardi & Partner Consulting GmbH in 2012, she has advised many multinational companies across various industries in Europe, Asia, and Africa for over a decade.

Lardi believes in the transformative impact of emerging technologies. She has developed deep knowledge and practical experience in a range of emerging technology solutions, such as blockchain, AI, virtual and augmented reality, 3D printing, Internet of Things (IoT) and sensor technologies, and robotics process automation, among others. She’s a teaching fellow at Durham University Business School and was the first chair of the Forbes Business Council Women Executives. She’s a dynamic and influential speaker and presents regularly at corporate and industry conferences. In 2022, she was recognized in International 40 Over 40—The World’s Most Inspiring Women by CapGemini Invent and Female One Zero. In her latest book, The Human Side Of Digital Business Transformation (Wiley), she delivers an essential and practical exploration of the human component and real-world implementation of digital transformation.

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