How technologies communicate with us - Natural Language Processing (NLP) (Case:Detroit Become Human)

Hi there! It’s Megi.

Today I will address one of my favourite examples when discussing future perspectives of Artificial Intelligence in life, particularly in marketing, which is a game by Quantic Dream named Detroit: Become Human.

You may have never heard of or played the game, so let me just say that this game’s settings are in a dystopian future Detroit of 2038, in which androids are integrated into everyday life as workers and companions. In this game, androids are machines, or robots, that closely mimic humans in appearance and structure; they are made out of biocomponents and plastic-like skeletons. They resemble people, freely communicate with them, and can easily make real-time decisions based on the initial settings of an android and of the current moment circumstances.

But their visual appearances, although fairly interesting, are currently not the focus of this particular video. This video aims to introduce the concept of Natural Language Processing (or, shortly, NLP) and its representation in this game, in real life nowadays, and its academic foundations. So, as an outcome of this video, you’ll be able to recognise the instances of application of this concept, and if you are looking for the topic of your research, you’ll be able to grasp the basics of this truly captivating topic and how applicable it is in marketing.

So, without further ado, let’s get back to our androids.

Throughout the entire game, there are different types of androids, and what’s notable is that they can communicate freely with humans. They quickly understand the inquiry from the human, process it, and either reply verbally or act on the required task physically. For example, they can process the evidence at the crime scenes, they can purchase and deliver the goods, tell a bedtime story to a kid, or discuss philosophical ideas with an elderly person.

Now, hearing about these activities, you may recall that even though we are currently not in 2038, in a dystopian future city of androids, we can have our technologies do these activities for us. For example, though your auto-procurement or subscription plan you can order the item at a particular time interval, the delivery robots can bring the purchase to your home, the voice assistant can read a kid a bedtime story, or it can voice the news or answer questions and discuss the different topics with different people. I’m not sure about the processing of the tangible evidence from the crime scenes as I am not close to this field, but I presume there is also a technological advancement for better database processing or computer vision and voice assisting. So, generally, these activities are currently completed by technology, even though there is no unification of them in only one piece of technology and their human-like physical embodiment.

While I can further discuss other aspects of AI use in these situations, let’s focus on the fact that technology can communicate with us based on our verbal requests. This is possible thanks to the emergence of conversational agents (or CAs) roughly since the 1950s-1960s [Weizenbaum 1966 [1], M. Adam et al., 2020 [2]] and strengthened their position of interest during the “second wave of artificial intelligence” [Launchbury 2018 [3], M. Adam et al., 2020 [2]]. With the overall technological development and further integration of technological solutions to marketing, chatbots became widespread and a focus of attention both from practical application and academic research. So, chatbots may act based on predefined scripts, providing customers with a limited selection of communication topics, or they can be “AI-based chatbots, which allow for diverse turn-by-turn conversations with human users based on textual input” [M. Adam et al. 2020[2]]. This type of conversational agent is close to what we see in the game and in real life with voice assistants.

But you may ask - so, how does the chatbot or the conversational agent actually understand me saying words, and what’s the place of the natural language processing in all of this? And what is the natural language processing exactly?

Well, here are the answers to these questions. Conversational agents can process textual and audio communication. So, basically, they can read, recognise and process the natural - human - language. The ability to do so is based on natural language processing, “which refers to the branch of computer science (specifically, the branch of artificial intelligence) — concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.” “NLP combines computational linguistics—rule-based modeling of human language—with statistical, machine learning, and deep learning models. Together, these technologies enable computers to process human language in the form of text or voice data and to ‘understand’ its full meaning, complete with the speaker or writer’s intent and sentiment.” “NLP drives computer programs that translate text from one language to another, respond to spoken commands, and summarize large volumes of text rapidly—even in real time.” Also, apart from what I’ve already mentioned earlier, NLP can be used in “voice-operated GPS systems, digital assistants, speech-to-text dictation software, it plays a growing role in enterprise solutions that help streamline business operations, increase employee productivity, and simplify mission-critical business processes.” [https://www.ibm.com/topics/natural-language-processing [4]]

But what about marketing use of natural language processing in particular?

If we do not go into details, NLP is used in, but not limited to, the following instances regarding marketing:

• Customer service chatbots of online business websites in browsers or mobile applications: for instance, they can help you search for a particular product or provide information on the status of your delivery

• Voice assistants, when you call the bank or any other organization, and they ask where they can redirect your call or assist in booking their services, or generally can understand your speech or your written inquiries

• NLP is used to determine trends and the ideas people share; it helps to control the reputation of the brand and what people say about the brand or the product; this collected information is further used to improve the customer experience, broaden the audience, and control for the communication channels

• Moreover, with the use of NLP, marketers determine frequent keywords searched and get a better understanding by analysing customers’ digital footprints

These fields are broad but nevertheless describe the trending and prominent directions of the use of NLP in marketing.

Of course, numerous risks and difficulties are associated with using NLP in marketing, but I will discuss them in future videos.

It is funny - how, from a tiny aspect of an android-focused game setting, it is possible to dive into the fascinating topic of academic research and the practical application of a concept that is close to our everyday life. And with this video, we covered just the basics of understanding. But I will be happy to share my knowledge with you further, so if you are interested, you can subscribe to my channel, browse other videos, and write your thoughts or questions in the comments or visit my website. I sincerely appreciate discussions, especially the topics I am fascinated about, so please do not hesitate.

Thank you for staying with me. It was Megi. Good luck, and see you in future videos!

[1] Joseph Weizenbaum. 1966. ELIZA—a computer program for the study of natural language communication between man and machine. Commun. ACM 9, 1 (Jan. 1966), 36–45. https://doi.org/10.1145/365153.365168

[2] Adam, M., Wessel, M. & Benlian, A. AI-based chatbots in customer service and their effects on user compliance. Electron Markets 31, 427–445 (2021). https://doi.org/10.1007/s12525-020-00414-7

[3] Launchbury, J. (2018). A DARPA perspective on artificial intelligence. Retrieved from https://www.darpa.mil/attachments/AIFull.pdf

[4] IBM. What is natural language processing (NLP)? https://www.ibm.com/topics/natural-language-processing]