I’ve been away for a while making what I hope is the last round of edits on my book. Your Data, Your Devices, and You: Easy-to-Follow Instructions to Reduce Your Risk of Data Loss, Device Infection, and Identity Theft is going live on July 1 on Amazon! It has consumed the better part of my free time for the past month. Now I have a bit of time back, until I start marketing. For now, I’ll pick back up on our exploration of Emerging AI Applications
YOUR OWN PERSONAL ASSISTANT
One major innovation that AI has supported is improved human-computer interaction. Natural language processing (NLP) enables computers to understand and process human language. NLP is exactly what it sounds like. Using, for example, ChatGPT, Google’s Gemini, or Microsoft’s Copilot, I can just ask the question I have instead of having to figure out what words to use in a search engine. I can provide a bit of background to support the question as well. For example, instead of typing “Things to do in <cityname>”, I can say something like this: “My husband, my son, his fiancé, and I are staying at a cabin on the lake in <cityname>. We’re going to do some fishing, but we would also like to find out what else to explore. We enjoy a variety of foods, exploring caverns, horseback riding, arts and crafts…”. This allows the tool to filter out things that are focused on small children. I could also indicate if someone in our party has any physical limitations, and I could fine-tune to give preference to things we really love, like historical museums. It’s just not possible to get this precise with a simple search engine. This advancement reduces the need for technical knowledge, allowing even non-tech-savvy individuals to effortlessly navigate and utilize their devices, thus broadening the accessibility and functionality of modern technology. This isn’t brand-new tech, though. We’ve been using it with Siri and Alexa (and their cohorts) for several years. “Siri, find me a hair salon in <cityname>.”
NLP can also analyze and interpret text data to determine the sentiment and opinions that are expressed by people. This can be beneficial for businesses to understand customer feedback, but it also helps them monitor their brand reputation, and they can more effectively make data-driven decisions that will help them improve their products or services.
While I wouldn’t rely on AI language translation for legal briefs or deep product instructions (unless I had verification from a human), for some basic situations, it does an adequate job. I used it when my husband was making some improvements to one of the buildings on our property. The contractor spoke some English, and my husband was confident he understood the basics of the request, but there were some things that we needed to get right in order to prepare for future improvements. Because there’s sometimes a language barrier between my husband and me (and we are both native English speakers), I had him tell me what he wanted, and I repeated it back to him to make sure I had it right. Then I typed it up and had him read it. Finally, I asked ChatGPT to translate it into Spanish. I speak a bit of Spanish, but not enough to articulate clearly what we wanted. I was able to look at the translation and see that the translation was accurate enough. It’s possible there may have been some grammar issues, but I wouldn’t have been able to find them. The contractor probably could, but most importantly, the contractor was able to read the translation and execute the instructions perfectly. In a business situation, breaking the language barrier can open communications for both buyers and sellers of goods and services, and it can provide opportunities to help patients in emergency situations, encounters with law enforcement, and a host of social situations.
Assistive technology to facilitate movement and device operation has been available for over a decade, but NLP improvements have enhanced the functions these devices can offer. Automation for lights, thermostats, window treatments, door locks, and more, can be engaged with voice commands as well as direct and wireless operation through a dashboard. The same technology that enables me to tell my car to call my son using my phone’s contacts and connection has been expanded to allow someone who has difficulty moving to control their environment for their comfort and security.
WHAT DO YOU RECOMMEND, JEEVES?
When you’re shopping on some large platforms, the recommendations based on past purchases is AI-driven. The recommendations for videos on your streaming platforms is, as well. It’s not quite as effective as getting a friend’s endorsement, but there’s no doubt that the user experience is enhanced by these recommendations, and you’re more likely to look at those recommended things that you would if they weren’t recommended. You’re at least more likely to go and look at something in addition to what you went looking for to start with.
When you’re on Amazon, the block that says, “Customers who bought this product also bought these other things” is generated by AI. It may suggest items that will enhance your experience with the original product you went looking for, things you may not have realized you were going to need, things that are sized to work correctly with the item you’re buying. They don’t always get it right, though. Sometimes what I see suggested “for me” doesn’t fit with what I’m buying at all. Streaming platforms also create curated suggestions based on what we’ve watched previously, and if you’ve ever wondered why you ought to give a rating to a movie or show you’ve watched, that’s why – so you can get suggestions of things similar to those items you really like. Again, they don’t always get it right – but then neither do my close friends. I had a friend suggest a movie that she thought I’d love based on the fact that I really liked another movie we’d both seen, and I didn’t like her suggested movie at all.
FRAUD DETECTION AND CYBERSECURITY
AI is already at work keeping us safer. Pattern recognition is one of the elements at work here. It’s the quality that helps computers see and understand patterns in data, just like how humans notice shapes, colors, or habits. For example, it allows computers to recognize a friend’s face in a photo, detect unusual spending on your credit card, or even spot a hidden trend in a lot of information. When your bank calls and says they’ve frozen your debit card because they detected that it was used at a gas station in Seattle two minutes after it was used at a grocery store in Miami, that’s sort of the results of an anomaly in the patterns. The activity didn’t fit the pattern, and the technology caught it. By leveraging sophisticated algorithms and machine learning techniques, systems can analyze vast amounts of data to detect trends, anomalies, and correlations that may not be apparent to human analysts. This capability is crucial in various fields such as finance, healthcare, and cybersecurity, where understanding patterns can lead to predictive insights, early detection of potential issues, and more informed decision-making. For instance, in cybersecurity, advanced pattern recognition can help identify unusual network traffic that may indicate a security breach, enabling quicker and more effective responses. If we had to spot these things manually, we’d never do anything else.
Real-time threat monitoring is essential for maintaining the security and integrity of our digital systems. It involves continuously observing network activity to identify potential threats as they occur, allowing for immediate action to mitigate risks. Here again, having technology do it gets it done well, and it does the job several analysts still couldn’t do in a timely manner. One of the key aspects of real-time threat monitoring is identifying malicious activity, such as unauthorized access attempts, malware infections, and data exfiltration. By promptly detecting these threats, security systems can protect user data from being compromised. Taking a proactive approach not only safeguards sensitive information, but it also enhances user confidence in the security of their digital interactions, fostering a safer and more secure online environment.
Next time, we’ll explore some newer AI uses, getting into healthcare, autonomous vehicles, and some of the latest advances.
How many ways are you using AI in your daily life? Drop a comment with a quick number, now that we’ve brought your attention to some of the “hidden” ways it’s already in your life.
[…] Part 1 […]
Permalink