Let’s say you are looking for accommodations for your next trip. You want an affordable place, with a fantastic balcony view, and an unforgettable experience. You then open up your laptop and start your research using search engines. The question is: how does the computer solve your problem?
The computer thinks with algorithms
First, it takes the keywords you type in as an input. Then it matches them with the database; the system has access to the computer then generates an output value as a feedback result to you.
It sounds simple. But imagine if it’s a human being. Imagine if you find 3 billion websites matching your keywords. How fast can you go? How effective can the process be? What is the false positive percentage?
One of the essential topics in computer science is about algorithms. It involves a sequence of instructions for solving a problem. The computer looks at your command or question as a problem and runs through multiple sequences to retrieve the results. For Google, in particular, it has the PageRank algorithm.
Translating business problems into algorithms requires sequential and numerical thinking. First, the computer should ask, “Does A = B?”. If not, the computer stops; if yes, it goes to the next question. “Does A = C?”. If not, it will stop, and if yes, it will go to the following sequence. Until in the end, the computer prints out a result. The way computers think is through a series of steps. It is very logical and calculative.
The exploration of artificial intelligence
Alan Turing is the father of modern computer science. He was successful in breaking the Enigma code during World War II. The Germans were using a cipher machine: ENIGMA for their communication. Turing invented Turing tests that at the core questions whether machines can talk like humans. He predicted that by the year 2000, computers would easily pass the Turing test. That was not true. The problem with communication is that a sentence could mean differently in another context, and sometimes there are no right or wrong answers.
In the 21st century, engineers and data scientists worked on Artificial Intelligence. Chatbots, smart homes, biometrics are a few examples to name. AI technologies require excellent performance, and that means the faster computers can perform, the better. The US and China compete in this race, and by 2018, IBM launched Summit with the speed of 148,600 Terra FLOPs per second. The goal is to ultimately apply AI technologies in different sectors, such as finance, medicine, and security, for better living standards.
Ideas for applying AI technologies
Technology made a difference in the way we do business. In purchasing orders, for example, customers would swipe their cards but would need to fill in a form if they want to join a membership program. With online shopping, the new Point of Sale (POS) system automatically asks for customers’ information and allows them to subscribe to a newsletter. Not to mention that the cost of computing has dropped drastically since the 1960s. In terms of speed, one Giga FLOPs cost 19 billion dollars, but in 2017 it cost 3 cents only. The advancement of technology enables us to do things more efficiently. That means you can let the computers do the computation, the data inquiring, and the menial tasks. So that you can focus on the critical thinking and decision-making processes.
IBM has published a white paper on how AI technologies can help to identify breast cancer. The study was an attempt to enhance healthcare technology. AI technologies may see unusual spots on an X-Ray that doctors might fail to see. They would be able to do so after learning from multitudes of data, checking with the doctors for feedback, and if they are wrong, they record their mistakes in their program and improve.
Microsoft created a Chatbot that interacts through Twitter social media. As mentioned, AI technologies process information by learning from what works and what doesn’t. In this case, Tay the Chatbot, unfortunately, adopted racism.
Lil Miquela is an AI influencer created by Trevor McFedries and Sara DeCou that, as of 2019, raised 125 million dollars investment. The AI portrays a 19-year-old artist and posts YouTube videos. While it raises controversy, Miquela questioned back if there’s a person on Instagram that doesn’t edit his or her photos.
Where you are on product stage matters
There are three product stages that you can focus on Early Stage, Mature, and Growth. In the Early state, you start offering your products and services and begin collecting data from your customers. The POS system previously mentioned fits well in this category. Technology enables us to ease the process of registration and purchasing items for customers.
In the Mature stage, we see how products improve by offering more services. Facebook started as a social media platform where you can connect with others and post to start a conversation. In 2009, Facebook launched the News Feed. In 2016, Facebook added Live Video. Later in 2019, Facebook gives more control to users with the ‘Why do I see this post?’ button. AI and emerging technologies can improve your product and services and enhance the customer experience.
Lastly, the Growth stage is about exploring different fields. Netflix was a subscription-based streaming service. Starting in 2012, Netflix offered “Netflix Original” in their catalogs. Here, they are becoming a producer and a movie distributor. What makes Growth and Mature different is that Growth is thinking beyond the current field. Mature companies focus on customer retention, while Growth companies would invest in new areas to grow their customer base even further.
AI technologies are here to help us
Cassie Kozyrkov, a chief decision scientist at Google, wrote in 2019 that strategies based on pure mathematical rationality without a qualitative understanding could be pretty naive.
On top of data collection, fast performance, and humanistic response, we need computers to be able to help us in making decisions. That includes the thought of responsibility, asking, “what would happen if I make this decision?”. Because at the end of the day, computers help us to solve problems and to perform an action based on our decision.
Current AI technologies perform well in repetitive tasks. It requires a lot of historical data to spot a pattern of processes and to predict the next best move. When you build products for customers, you need to consider how technology can assist them. Where there is a repetitive task, you can use AI technologies for a better result.
When you build products for your customers, you need to consider how technology can assist them. To adopt from UX Design’s terminology, it’s all about the user journey (read more on our previous post). Break down the steps where a user interacts with a technology device. Think about their inputs; think about the computer’s way of thinking. At the back of your mind, think about AI emerging technologies that can ease the process. Then define what a positive experience you want the customer to experience through your business is. Work your way to help them make a better decision. In other words, go a step further to build a relationship with your customers. Implement the technology in different platforms, including web apps, mobile apps, voice-over commands, chatbots, etc.
The user: is it for employees or customers?
As you develop your apps, think about the users who will use the technology. The shopping experience is an excellent example of a customer-facing app. Someone would visit an online store, browse around, select items to buy, go to the cart, insert data about the card and address, click the purchase button, and receive a receipt. The priority is for customers to get the best experience with the app: fast, reliable, and easy to use.
Meanwhile, an example of an employee-facing app would be on the operation side. In a doctor’s visit, patients would need to wait in a queue to meet a doctor. When they get to meet the doctor, the patient goes through an examination and receives advice from the doctor. What if this process can be more efficient? A useful tool would track the time spent during registration, during the waiting time, during the examination, and during the advising. An app could help ease the registration, and AI technologies would help identify symptoms faster. The hospital then can work more efficiently and focus more on critical thinking, empathy, and ensuring comfort to patients.
How AI technologies can help during the downturn
It is inevitable to experience an economic downturn from time to time. We know about the 1997 Asian financial crisis and the 2007-2009 subprime mortgage crisis. In 2019-2020, the world expected lower GDP production due to the COVID-19 pandemic.
Companies should then focus on what matters in their businesses. With AI technologies, you can identify inefficient processes, you can streamline customer service, and your overall performance will be better. There is also a trend of the declining cost of cloud infrastructure that would help you invest more in AI technologies.
You can also think about implementing AI on different platforms. That being said, you need some expertise in user experience design strategy, user research, rapid prototyping, and app development. While you may have an internal team but do, they have the bandwidth or the expertise? Companies of all sizes work around this challenge by working with experts who are successful in delivering results.