Artificial Intelligence and its Customer Value

Chitralekha Das, AI Enthusiast, Senior Program/Project manager, Intralinks
288
511
109
Chitralekha Das, AI Enthusiast, Senior Program/Project manager, Intralinks

Chitralekha Das, AI Enthusiast, Senior Program/Project manager, Intralinks

Artificial Intelligence (AI) is a natural extension of human intelligence. While AI has been around for a while, it has become so ubiquitous that it touches every one of us in some shape or form. There are numerous resources that capture how AI can benefit companies. Be it driving up revenue-through customer discovery, analytics, driving down costs–through increased efficiency, cost reduction, or improving customer satisfaction-through a better user, and customer service experience.

This article is from the viewpoint of an AI consumer or user, the final recipient of this technology.

Quick Introduction to AI:

Machines have been there for a long time and have been helping us with everything, from commonplace things like cleaning the house to detecting threats. Artificial intelligence is the technology that allows machines to perform tasks that normally require human intelligence. According to Gartner, Artificial Intelligence to be the most disruptive technology of our era, particularly machine learning (ML) and Deep Learning (DL), which are subsets of AI.

Machine Learning (ML)—the machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it’s given. Within just the past few years machine learning has become far more effective and widely available.

Deep Learning (DL)—the machine’s ability to sift through massive amounts of data to find patterns and get smarter over time. It involves the construction of artificial neural networks, using software and complex algorithms to recreate the capacity of the human brain to learn. The science of deep learning, a sub-discipline of ML, is only a recent development in the grand scheme of things, but during its short existence, it has been producing some impressive technological achievements.

Using machine learning and deep learning techniques, we can now build systems that learn how to perform tasks on their own as well as find patterns from millions of data.

 By being more educated and aware about AI, we can ensure that it realizes its full potential  

Benefits of AI:

Though the full potential of AI hasn’t been harvested today, here are some recognized benefits to a typical AI consumer or user.

Examples:

Customer Service powered by AI: Many companies are implementing bots powered by AI to work in their contact centers and communicate with their customers. AI is even helping to predict customer behavior, providing advice to customer service agents on how best to solve a particular issue. This is helping the service agents know their customers better and feel empowered and smart (or superhuman) about their job while helping customers. At the other end, customers are getting personalized, faster and efficient service which improves their lifestyle and productivity and keeps them happy.

Recommendation engine powered by AI: Recommendation engines are used in a wide range of industries to improve the customer experience by trying to intuit what the user wants to do next. Many companies like Netflix, Amazon, YouTube, and Google are implementing AI powered recommendation engine in different contexts—whether it’s a movie, news content, or a video or a shopping list recommendation. This not only saves time spent on searching the internet, but also provides rich and appropriate content or new areas which customer/user might not have thought of in the same context.

Early detection of diseases: Using deep learning, companies like IBM and Google have been able to make breakthroughs around early detection of diseases such as cancer, cardiovascular disease, and diabetes with greater accuracy. For instance, IBM has been able to use AI to predict heart failure. Google created a neural network that could analyze medical images and identify tumors (breast cancer) with a greater degree of accuracy than human pathologists (89 percent vs. 73 percent). As one can imagine, this has wide-ranging benefits. This improves the overall survival rate by catching diseases earlier thereby giving a better shot at treating it, reduces misses during to human error, and reduces the load on the medical network.

Concerns with AI:

While AI can be beneficial to human race, it poses several ethical and data privacy concerns, the common ones being:

User privacy: As we know, AI uses data to train its models. To provide a personalized prediction/suggestion, it needs to understand the customer/user behavior—what they like and dislike, what attributes trigger certain type of actions, etc. So, companies scrape user related data to train AI models. The dilemma is not only whether companies should use the user specific information for predictions/suggestions but also what type of user information, for what purpose and to what extent. An example would be targeting shoppers with a recommendation of shopping items or helping medical discoveries by studying user specific data such as behavioral patterns for eating, exercising, sleeping etc.

Mistakes by AI: Like human, there is a possibility that AI can do mistakes as it relies in data to train its models and there could be instances whether the data is not diversified enough while training the AI. As the machine learns from the data and optimizes its models itself, it’s difficult to troubleshoot. So the question is how can we guard against its mistakes? With all of the successes of AI, it's also important to pay attention to when, and how, it can go wrong, in order to prevent future errors.

Bias inherited in the model: AI uses data to train its models. If the input data has bias, then the prediction or outcome from the AI will have the biased output.5 unexpected sources of bias in AI. As AI is being used in talent acquisition and healthcare etc, it could be dangerous to the human race if a careless approach is taken. So, the big question is how can we make sure the models are well diversified and eliminate bias?

Job security concerns:  There have been fears that automation will kill more jobs. An estimated 5 million U.S. factory jobs have evaporated since 2000 and most of those (88 percent) were lost to increased productivity due to automation, according to a study by Ball State University. A recent report by consultancy PricewaterhouseCoopers estimates that 38 percent of U.S. jobs have a "high risk" of being wiped out by automation by 2030. So the question is will smarter machines cause mass unemployment? Or are we talking about a disruption in the labor market which needs workers to learn new skills much faster than in the past?

Fear of machine taking over human: Though artificial intelligence will be disrupting businesses and benefiting the human race, futuristic leaders like Elon Musk have been cautioning on regulating AI for the welfare of the civilization from the danger of machines and urging to ban the use of AI in weapons.

While we consider these risks, we should also keep in mind that, on the whole, this technological progress means better lives for everyone. Artificial intelligence has vast potential, and its responsible implementation is up to us. As we have seen throughout mankind’s evolution, technology is a double-edged sword. By being more educated and aware about AI, we can ensure that it realizes its full potential. 

Read Also

Identifying Technological Requirements Prior to AI Implementation

Identifying Technological Requirements Prior to AI Implementation

Kumar Srivastava, VP, Product and Strategy, Machine Learning, Artificial Intelligence, BNY Mellon
AI: Accelerating Decision-Making

AI: Accelerating Decision-Making

Nigel Duffy, Global Innovation AI Leader, Ernst & Young LLP
Machine Learning and Artificial Intelligence: Revolutionizing the Physician/Patient Relationship

Machine Learning and Artificial Intelligence: Revolutionizing the Physician/Patient Relationship

Kali Durgampudi, VP of Innovation, Mobile Architecture, R&D, Healthcare Solutions, Nuance Communications