Artificial Intelligence and Machine Learning for Business delivers a simple and concise introduction for managers and business people. The focus is on practical application and how to work with technical specialists (data scientists) to maximize the benefits of these technologies.
This revised and fully updated fourth edition contains several new sections and chapters, covering a broader set of topics than before, but retains the no-nonsense style of the original.
Steven Finlay is a data scientist and author with more than 20 years’ experience of developing practical, business focused, analytical solutions. He holds a PhD in management science and is an honorary research fellow at Lancaster University in the UK.
Targeted Age Group:: 11+
What Inspired You to Write Your Book?
I like to talk to people about what I do and have always enjoyed writing simple, non-technical books that help more people to understand what Artificial Intelligence and Machine Learning are.
The challenge I most enjoy is trying to translate what can be complex mathematical subjects into something that is non-technical, without any formulas or equations, and can be understood by anyone regardless of their background.
The use of artificial intelligence-based technologies has exploded in recent years. AI is being used in almost every walk of life to improve processes and enhance peoples’ everyday experiences via “Artificially intelligent” machines and computer interfaces. Amazon’s Alexa and Google Translate are two well-known software products that demonstrate the benefits that these technologies can deliver. Likewise, facial recognition systems, predictive texting and setting the interest rates on credit cards are further examples of where AI-based technologies are routinely being applied in the real world.
Many products and services are also adaptive. They tailor their responses to the behavior of individual users. TV and music streaming services learn to identify the content you like and present you with recommendations that you’ll no doubt be interested in. Change the type of music you listen to and their recommendations will change too. Likewise, you can buy heating systems that learn to anticipate when it’s the best time to turn the heating on so that you don’t have to bother, while at the same time optimizing energy usage to reduce your bills. These types of service, that continually learn and adapt, are further examples of artificial intelligence in action.
This concise text provides a managerial (i.e. non-technical and no complex equations) overview of artificial intelligence and machine learning, what they are and how they’re used. No prior knowledge is assumed. To put it another way, if you can read and write and do basic arithmetic (there is a bit of arithmetic, but not that much) then you should be OK with the material in this book.
A good question to ask at this point is: Why do I need to know about these things? One reason is personal. AI has become the primary tool that organizations use to leverage the data they hold about you. They use AI-driven tools to predict how you are likely to behave under different circumstances, and hence, the way they should treat you in order to maximize their (and sometimes your) objectives. They use these systems to decide if you’ll receive a great offer or a poor one, if you should be placed at the front or the back of the queue, if you’ll be treated as a suspect in a criminal case or how much you can expect to receive when you make an insurance claim. Therefore, it’s not a bad idea to know something about these things so that you can understand why an organization may have treated you one way and not another.
The other reason to learn about artificial intelligence, and the one that’s the main focus of this book, is that it’s now a mainstream business tool. Not that long ago, artificial intelligence was the domain of a few nerdy specialists working mainly in academia or tech start-ups in Silicon Valley. These days, regardless of what business you are in, applications of artificial intelligence can be found across the full range of business activities. This covers everything from short-listing CVs to help HR professionals decide who to hire/fire, chatbots answering customer queries, to robots on the production line, warehouse management and customer deliveries. As a consequence, artificial intelligence is supporting or supplanting humans in many domains.
Artificial intelligence has arrived big time. It’s no fad and it’s here to stay. Those organizations that are using it to solve business problems, improve efficiency and cut costs are benefiting at the expense of their rivals.
This doesn’t mean you need to learn all the things that a technical specialist (a data scientist) needs to know. However, having a working knowledge of what artificial intelligence and machine learning are, and knowing how they can help your organization to deliver better products and services, will be beneficial. Not least, because in order to make effective use of these tools they need to be focused on business objectives to address specific problems that organizations face.
If, on the other hand, you happen to be an equation quoting, formula juggling, bad ass mathematical genius who thinks they know all there is to know about artificial intelligence and machine learning, then this book may also have value for you too. Possibly, a lot more than you might think. Why? Because if all you focus on are the computational aspects of the subject, then you face a real risk of hitting a brick wall when it comes to delivering useful solutions in the minefield that is the real world; a world populated with social, ethical and political issues. This, together with a growing raft of privacy and data protection legislation, could derail your solutions no matter how good they are mathematically. Without consideration of these “Soft issues” the best case is that the solutions you develop don’t get to be deployed. The worst-case scenario is that you design an artificial intelligence-based system that lands you in court because it unfairly discriminates against minorities, women or some other group of people.
Almost everyone acknowledges that artificial intelligence has the potential to deliver immense value for businesses and, almost daily, there’s another news story about some wonderful new application of AI that’s going to save lives or boost profits. However, the rather sobering finding, from a number of studies, is that:
Most business-focused AI projects fail to deliver
The reason why so many organizations fail with their AI projects is predominately due to a lack of understanding of these broader social and organizational issues rather than any failings in the underlying AI-based technology being deployed.
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