As Artificial Intelligence plays a vital role across different industries, including healthcare and education, the debate on the implications of the biasness and consequently the role of fairness into AI algorithms has been crucial. Unconscious and societal biases often emerge in decision-making, a human flaw that is often overlooked in the widespread perception of AI as a purely mathematical and objective concept. To build a successful, sustainable AI model, it is essential to think about ways to involve the entire organization in building AI. Consequently, engaging all employees — not just those with technical competencies — in the development process ensures that AI solutions truly augment employees in their current roles, drive productivity and efficiency at work, and incorporate cross-functional insights informed by a diversity of perspective.
Involving the workforce in these efforts is instrumental; with AI reshaping the future of work, fluency with its functions is now an essential skill. With the pandemic hastening our dependence on the digital realm in some capacity or the other, we can all do with introductions, refreshers, or more profound exploration into what AI means to us. I would like to share some of my favourite literature that has chalked out how AI is defined, how it has evolved, and what its implications are in our life.
If you are an AI beginner, I would highly recommend these four books on AI & ML:
1. Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos, published September 2015
Simple, direct, and lucid — Domingos’ 2015 book on the past, present, and future of different machine learning algorithms is an informative, easy read. The book provides you with, as the author states, “a conceptual model of machine learning”, defined appealingly as “a technology that builds itself”. The book begins with the first years of computing science, where the programmer held the sole key to an algorithm’s success and developed the story of how this has changed with the growth of data and advancement of the self-learning inference-deriving capabilities of AI. This book is ideal for readers interested in the machine learning world, its scope, and the possibilities and challenges that it wields. It also guides the reader to look ahead for future research in AI and Machine Learning and is an excellent introductory resource for the rest of the titles in this list.
2. AI Superpowers: China, Silicon Valley And The New World Order By Kai-Fu Lee, published September 2018
Lee is a prolific academic, businessman, and with this book, author — here, he shifts the usual dialogue on AI that centres western concerns to exploring China’s growing stake in the field and the global eco-political exchanges that arise as a consequence. Further, he calls for compassion and repositioning of perspective to see AI as a tool that benefits humanity as a whole, rather than as the agent of a dystopian future rife with economic inequality and global unrest. No matter what your previous exposure to the technology has been, Lee seeks to help you better understand the vision of an AI-altered future. Personally, the author’s analogy of relating AI to something as indispensable as electricity, with data being the fuel that drives the engine, has resonated with me. I find that this book captures both incisive and inspiring notions for the future — a clarion call of caution mixed with an articulate voice of hope and courage — certainly worth a read to understand the threads that tie AI to our global systems, all through the eyes of a veteran in the field.
3. Human + Machine: Reimagining Work in the Age of AI By Paul Daugherty and H. James Wilson, published March 2018
Hearkening back to the introduction of this essay, this book re-conceptualises the human-AI relationship by investigating new developments in collaborative machine learning — the organic partnership of humans with advanced AI systems. The authors emphasise that humans and intelligent machines are working more closely together than ever before; this is rapidly changing how companies operate across all functions of the business. They go on to establish six hybrid Human+ Machine roles that embody this reimagined and integrated culture of work, positing that every business must put these in place to capitalise on the AI revolution that is already in full swing.
4. The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity by Byron Reese, published April 2018
Another influential work on AI’s history and progress, this book discusses three previous ages, outlining how and why technology reshaped humanity and set up AI as the fourth age of transformation. He takes a multi-pronged approach to some of the most profound questions of our time, adeptly marrying the study of history and human civilisation with the gradually accelerating independence and intelligence of our technologies, marking the epochs that defined shifts in this progress. Those who like to blend cross-disciplinary insights in their study of the field will find Reese’s references and narrative particularly refreshing. Inviting readers to make their own choices, this book is an ideal read to explore advancements in AI’s role and what these will mean for us as a species.
While these works are comprehensive chronicles and studies of the history and real-time development of AI and ML, we must remember that we are still in the infancy of AI proliferation — there is much more research to be done and progress to make.
For now, we can start by educating ourselves and championing for equity of involvement in the development of AI and ML; if I have to leave you with a gentle reminder, it would be to keep reading and stay curious!