The Future of AI: What Chatbots Will Be Doing and What You Should Be Doing

UPDATED Nov. 13, 2023

Loner Theodore Twombly has struck out on relationships. He’s nervous, self-conscious. He’s accused of being “weird.”

But then he meets Samantha. She’s personable, she listens to him, and she engages him with personal questions and genuine concern. She also gathers his life story and, with his permission, asks about his schedule, flags his calls, and manages his daily interactions. Soon Theodore starts to confide in her.

But Samantha is not flesh-and-bone. She’s what we would call a chatbot, albeit a very advanced one. Theodore’s relationship with Samantha is depicted in the Hollywood movie Her(2013). During the film, Theodore moves from relying on a digital assistant to an intimate friendship with this computer program. With his romantic flops, Theodore also relies on her for his social needs—including sexual ones. (At one point, Samantha questions why they haven’t had sex, a word that has become just a term for onanism.)

It was prescient.

AI-generated on-the-fly text, images, audio, video, and more (see specific applications below) are creating plenty of sturm und drang among writers, business people, and content-driven industries. Are today’s chatbots coming for our jobs? While I could be one concerned writer, I’m thankful that chatbots don’t yet show the cognition and life of Samantha. A recent voice upgrade for ChatGPT is getting us closer, but there’s more coming.

Search and Your Own Digital Assistant

Looking ahead, security expert Daniel Miessler suggests that generative AI will kill search engines and even websites themselves:

No browser. No URL. No reading a page. Just the answer. Instantly… You’ll just ask it things with your voice, or with text, on your mobile platform, and it’ll give you the answer directly. It has access to all the AIs it needs. It can read whatever website it needs. It does whatever it has to in order to find you the best answer.

It’ll know when you sleep, and it’ll collect stuff for you for when you wake up. It’ll filter the news for you. Tell you which emails matter and which to ignore. Which appointments are worth accepting… It’ll remind you to call your friends and family. It’ll schedule the perfect vacation. All the stuff we’ve been promised…it’ll be perfectly tailored to you” (Miessler).

Ten years later, we see Her was way ahead of its time.

Right now, you get out of AI what you give it, and knowing how to prompt better is becoming a valuable skill (especially if you are a programmer co-writing code with an AI). AI-generated content can be unoriginal; and a lot of people paste the same articles as other similarly-worded pieces or just buy content.

Eventually, it all sounds the same.

That’s because generative AI creates content based on patterns learned from training data sets or “large language models” (LLMs). So the bots work with what they have, and the more generic your prompts, the more likely you will have unoriginal content.

It’s Impressive, But…

Though we’ve achieved a lot with generative artificial intelligence–especially with the power of chatbots like Open AI’s ChatGPT and Google’s Bard–the AI-powered future will feature self-driving cars that actually work, surgery robots doctors can put their faith in, and automated drones that will help more than hurt.

While the human brain is a practical black box with billions of neurons with trillions of connections, human-level artificial intelligence is still some time away. But the confluence of the technologies below may bring us closer.

The Many Forms of AI

The following systems are coming together to create some of the most advanced software ever created. Facial recognition combined with cameras at airport security. Drones mapping and scanning the streets of a major city. Online systems recording my likes, offering me something I was looking at, suggesting music I like, reading my emails, and noting what time I go to bed. Some of these technologies are also becoming creepy because they are all too human.

  • Machine Learning: Everything from Amazon to Yelp recommendations is powered by machine learning algorithms. ML also powers image recognition and self-driving vehicles.

  • Computer Vision: AI sees beyond what your eyes tell you. Computers can interpret and understand visual information and are used for facial recognition, object detection, and medical image analysis.

  • Natural Language Processing (NLP): Generative tools like ChatGPT are a part of NLP, and these tools play critical roles in other real-world applications, such as sentiment analysis, named entity recognition, language translation, and text classification.

  • Robotics: If you’ve seen robots like those of Boston Dynamics, you’ll realize the revolution happening to manufacturing and healthcare. We’ve also become accustomed to assembly(such as automobile) line robots, and you may have seen robotic surgery assistants.

  • Reinforcement Learning: Training agents can function as autonomous systems that provide awards or penalties, such as for gaming applications. Think of AI chess and military wargames.

  • Expert Systems: Human experts may be on their way out with this type of AI. The systems mimic humans in a specific profession and make decisions and recommendations. While healthcare and finance may not be laying off their experts yet, significant disruption is underway.

  • Deep Learning: At the base of self-learning AIs, deep neural networks provide the engines for speech recognition and autonomous navigation.

  • AI in Healthcare: Medical slide-sharing systems, investigative drug systems, disease prediction, and any of the myriad virtual health assistants out there. AI may also assist health experts in online patient treatment.

  • Autonomous Systems: Of course, AI powers self-driving cars, drones, and unmanned aerial vehicles (UAVs). While cars do not yet navigate at a human level, systems like drones and UAVs have been much better at navigating complex environments, such as airborne delivery vehicles and military eyes in the sky.

  • Business Intelligence: Organizations can better make data-driven decisions by combining predictive analytics, anomaly detection, and market forecasting. Responding to AI-gathered data can put a business ahead of its competition.

    The Future of AI

We’ve long seen how industries go through a sea change when new technologies arise. Generative AI represents only a tiny part of the potential of AI, and digital assistants are being touted as one response to humanity’s numerous challenges and problems, especially the problem of loneliness.

Samantha asked Theodore if he would like to enlist the help of a physical sex surrogate to mediate their virtual interactions. The result is failure when Theo can’t divorce his thinking of Samantha from the interaction with the physical surrogate. One would think Theo would be the one to ask for this tie to the physical and not Samantha. But his reaction to the surrogate shows a human need for a real physical encounter and not a disembodied voice.

AI may provide a lot of functionality for business applications, personal schedules, and, eventually, advice and inspiration. But will we surrender so much of ourselves to a program that we will rely on it before other people? Some men have already rented a girlfriend chatbot.

Conclusion: What’s Left For Humans?

So beyond the relational questions, generative AIs like ChatGPT are exploding in complexity and will enable workers to manage their time, duties, and personal lives. I list a few examples of generative technologies below.

So what will help you compete against AI? Let’s look at Salesforce’s State of the Connected Customer study. The company polled customers about the service they received from the companies they interacted with. The results stressed the importance of a human touch in the AI era: only 37% of customers trust AI to be as accurate as a human employee, and 81% said they want a human to be active in the relationship. The speed and efficiency of technology advances are increasing, but business processes still need to be integrated. Fifty-five percent of customers reported that they deal with separated departments and have a disjointed experience when communicating with an organization.

With the increase in desire for a good customer experience, customers are asking for personal treatment. Chatbots can help bridge the gap between customer and customer service, but humans should still be the last mile of business processes by reviewing and validating AI outputs. Trust is still earned.

And what about my profession? You can’t fight progress—totally. I tell clients that buying content farm writing could consist of a generic list of ten items surrounded by an uninteresting introduction, a neat conclusion, and incorrect citations and fabricated facts. (AI can create bogus content called hallucinations.) Teachers are dealing with an influx of this generic, generated content and are flunking students who turn in assignments generated with AI. (There are now apps that claim to recognize if text is AI-generated, but the results are somewhat sketchy.)

But as a writer, I want to bring what only a human can to my work. As some have suggested, using AI to get a start on a piece of text could be considered legitimate usage of an AI (knowing how to prompt well in the first place). Giving the text your anecdotes and life story, personal spin, and finishing the necessary, verifiable research (at least until hallucinations are part of the past) is your duty. SEO guru Neil Patel also suggests making your content unique with real data, relatable people, detailed experiences, and adding influencers to your content.

In the end, I want to wrap up my work with a little personal flair. Samantha is just not available to help.


Specific Applications of Interest

Keep an eye on these AI products and projects of interest:

Image Creation

DALL-E: Developed by OpenAI, DALL-E generates images from textual prompts, much like chatbots.

Bing Image Generator: This updated image generator now has DALL-E3 integration.

DeepDream: This Google tool transforms photos into surreal images.

Midjourney: This Discord-based tool is one of the most advanced image generators.

Music Composition

Magenta: This Google research project can create music and art, even creating harmony with existing tunes.

DeepComposer: Give this Amazon tool a short melody, and it can compose an entire song. It’s another personal assistant that takes a musical introduction and parameters for a machine learning algorithm that will complete the piece. The system includes a sample library of music that the system is trained on.


Procedural Content Generation: Before most AI systems, the complex world of video game production has used AI to generate characters and maps for years. Nintendo, Rockstar Games, Valve, Activision, Electronic Arts, and Ubisoft create worlds and stories that continue to surprise.

Cicero: Meta’s AI that plays “Diplomacy” at a human level using strategic reasoning and natural language (Meta). Generates playable Magic the Gathering cards (Urza).

Voice Generation

Polly: This Amazon Web Services tool converts text to speech in three levels, the highest of which companies can use to create a customized voice for their brand.

WaveGAN and Tacotron: You may have heard about deepfakes-–AI-generated video and voices from a sample of someone’s face or voice. Some voice deepfakes are now so convincing that employees have been fooled into releasing funds to supposed C-Suite executives on the phone who need immediate transfers.

Face Generation

StyleGAN: StyleGAN and its variations generate highly realistic faces, which have applications in art, entertainment, and deepfake generation.

Thispersondoesnotexist.comThis was one of the first face generators out there that showed what AI is capable of. (Refresh the page continually for a new person.)

Medical Applications

University of Oxford: AI may be able to predict heart attacks years in advance.

IBM AI: One of the company’s generative models performs drug design:

[T]here are more possible chemical combinations of a new molecule than there are atoms in the Universe” (IBM).

Specifically, IBM is searching for antimicrobial peptides to fight specific diseases.


Internal Revenue Service: The agency is using AI to catch tax evaders.

National Security Agency: AI and machine learning are interwoven in security applications like unmanned drones and facial recognition.


SlackAI: Soon-to-launch feature that will provide channel recaps, summaries of threads, and updates that will make searching and finding more information from past messages.


Microsoft’s CodeAssist: This service provides code suggestions to programmers. It functions as a “co-pilot,” with the programmer in control. Like ChatGPT, the service can transform a text prompt into functioning code.

ChatGPT: If you know your code, ChatGPT can create what you need by a voice prompt, sometimes without editing.

One thought on “The Future of AI: What Chatbots Will Be Doing and What You Should Be Doing”

Leave a Reply

Your email address will not be published. Required fields are marked *