Very few organizations provide consistently stellar customer service. Customers expect organizations to tend to their needs, and if the organization fails to do so, there is a chance that the customer will chose to instead spend money on a competing or substitute product. Some organizations have attempted to implement artificial intelligence in call centers as a way to reduce labor costs and streamline customer service processes. However, as many of us are far too familiar with, artificial intelligence in customer service hasn’t lived up to the hype. The first example that comes to my mind is Amtrak’s “Julie,” who fields all of Amtrak’s calls to get basic information before transferring customers over to an agent. There has not been a time where I haven’t had to read my six-character booking number to Julie at least five times before she finally understood all of the characters. I’m upset before the system even has the chance to transfer me to an agent. Amtrak’s Julie represents a traditionally reactive customer service model, where the customer reaches out to the company with an inquiry, and a support agent reacts to the inquiry. Salesforce & Cisco flipped the traditional customer service model upside-down, and recently partnered to help organizations use data to become more proactive when it comes to customer service. The two technology conglomerates bring together Salesforce’s Service Cloud and Cisco’s Contact Center to create a single agent desktop, where the agent is empowered to quickly handle every customer interaction with personalization and data-driven insights. All customer inquiries come through the Contact Center platform, where Service Cloud intelligence automatically classifies the case based on user history and trends. Contact Center then routes the call to the agent best equipped to tackle the case, along with recommended responses and rich details on the customer from all departments within the company. The more the agent uses the system, the smarter and more predictive it becomes, all benefiting the customer in the end of the day. By merging two major platforms in to a single desktop solution, Salesforce and Cisco bring new-market disruption to customer service. Has anybody experienced stellar customer service that somehow incorporated artificial intelligence? How else do you think artificial intelligence or tomorrow’s high tech could impact the future of customer service?
Consumer motivation trends in the beauty industry are shifting, and more than ever personalization is the key to modern day customer loyalty. Despite the millions of products on the market, the beauty industry overall has an utter lack of personalization, but artificial intelligence just might be able to change that. Companies are now starting to embrace the uniqueness of each customer, and creating personalized products designed specifically for the individual consumer. New technologies, such as machine learning and artificial intelligence, increase the level of personalization companies can achieve.
Earlier this month, the French cosmetics group L’Oréal announced its acquisition of the Canadian beauty tech company ModiFace. ModiFace is one of the biggest names in BeautyTech today, and has developed over 200 beauty apps for more than 80 brands. Such apps include cosmetics tryout apps and chatbots for Estee Lauder Cos., Smashbox, Allergan, and Coty; Clairol’s 3D hair color simulator; and Sephora’s ColorIQ and upcoming LipIQ technology. This acquisition will allow for L’Oréal to produce more digital services, such as tools to allow customers to test out various beauty products virtually, through augmented reality and artificial intelligence. More specifically, the company is looking to produce an app that would access the user’s camera, so they could try out makeup virtually and in real time. Throughout its existence,L’Oréal has acquired many cosmetics companies, but this would be the first tech company it has taken over. This type of acquisition from such a large player in the beauty industry has the potential to spark the digital acceleration of the industry as a whole.
A question I have is, in what other ways could technology be useful for the cosmetics industry? Is this the extent of it, or do machine learning and artificial intelligence technologies have the ability to truly transform the beauty industry?
When discussing AI, many focus on the incredible suite of functionalities that the technology can bring to the table to make our lives easier, such as the capabilities in personal assistants and self-driving cars. However, in order for these functions to take place and provide the most utility to human users, the AI behind it needs to be built to learn and execute its functionalities in a way that aligns with human end user success metrics and standards. This is where the concept of AI alignment comes into play. AI alignment is the study and practice of building out AI utility functions to be in line with our own. This practice requires the designer to establish a detailed point system that assigns points based on the positive or negative utility that the human end users realizes based on the outcome of specific actions. If there is too little detail, then negative outcomes can come about.
A simplistic example of AI misalignment can be seen in Disney’s Fantasia, where Mickey Mouse brings to life a broom and orders it fill up a cauldron. There was not sufficient detail inputted in aligning the broom to this task and it ends up flooding the room. The utility function in this case can be summarized as “If cauldron is full = 1 point, If cauldron is empty = 0 points”. Now, if we were to apply AI alignment principals to this situation, the function would include more details to align the intelligent agent’s values with that of the end user such as “If room floods = -10 points, If someone dies in the pursuit or result of this task = -1,000 points, If task can be completed in 10 minutes = +0.2 points, etc”. By adding additional nuance, the AI is able to complete the task as intended by the end user without leaving room for unintended consequences.
What are some other examples of proper or improper AI alignment in technology today? How can integrative thinking be applied to AI alignment? How do differing cultures impact deriving end user utility?
Ride sharing apps like Uber and Lyft were so disruptive in nature and changed consumer behavior to such an extent that a new type of “sharing economy” seems to have formed around them and similar applications. The key features of the applications are their affordability and the access provided to this type of “on-demand transportation” that essentially became democratized. Despite the widespread use of these apps, their business models may prove unsustainable. According to the BloombergView, “Eighty percent of [Uber’s] $9.7 billion in quarterly revenue was eaten up by a combination of driver payouts and bonuses, along with discounts to riders. Toss in insurance costs, and you’re up to 90 percent—and that’s before spending on marketing, research and development, overhead and so on”. Without the aid of venture capitalists, Uber will be in huge financial distress in the future. However, the firm does not operate as one that is concerned about future financial uncertainties. In fact, Uber is one of the many firms conducting research on and testing autonomous vehicles. Could this be its long-term strategy that will make its business model viable? Will the firm be able to weather these challenges long enough to see its investments in A.I. pay off?
Artificial (AI) is becoming the new “it” thing to invest in among technologies, and it has caused several disruptions to the technology industry. AI is a human-like computer tool that enables them to run large sets of data and self-learn different algorithms. They can also help companies make decisions in quicker time with higher levels of confidence. AI has become so popular of the past couple years due to a few reasons. All algorithms live in cloud based environments, something all companies have been switching over to. The cost of data has decreased 38% over the past few years, allowing companies to buy more and collect more data. The final reason why AI has become so popular is because investors are throwing billions of dollars in startup companies that focus on AI. All of this has started to see some true disruptions to the technology industry. We have seen AI implemented in sustainable updates, like YouTube and Netflix, to help give us more personalized recommendations. Both companies have reported an increase in viewer watch times. Perhaps the most prominent area we have seen AI take place is in a completely new market. AI has led to the creation of digital assistants like Siri, Alexa and Google which in turn have created products like Echo and Google Home. There is money behind these new speakers too, Amazon, creator of echo, currently holds around a 70% market share in what is soon to be a $25 billion market. AI isn’t going to stop at software updates and digital assistants it is starting to take over the marketing and health industries as well. What do you think is next for AI? Do you think AI is here to stay or just waiting to be phased out by the next innovation? Where would you like to see AI go in the next few years?