Machine learning is a specific subset of Artificial Intelligence (AI). In my interview with Christopher Penn, who is an IBM Watson Machine Learning Professional, among many other industries, we (barely!) dipped into a bit of his expertise to uncover not only terminology but scale and possibilities of machine learning and AI. AI is a broad term that encompasses the teaching of computers to perform tasks that typically require human intelligence. It includes tasks such as understanding spoken language, processing natural language, and recognizing and comprehending images through computer vision. AI serves as an umbrella term for various technologies and techniques that enable machines to carry out these tasks.
Machine learning refers to the process by which machines learn to perform intelligent AI tasks. It involves training machines using large amounts of data and algorithms that allow them to recognize patterns, make predictions, and improve their performance over time. Machine learning is a key component of AI, enabling machines to acquire knowledge and skills without being explicitly programmed for each specific task. We will discuss types of machine learning, accessibility, ethical issues and opportunity.
Types of Machine Learning
Large language models like ChatGPT are not really designed to be used like a search engine. They are designed to structure and restructure text. That’s why they’re called a large language mode. They are good at extraction. For example, you can give it a whole bunch of emails and tell it to extract the key points. They are very good at summarization, especially if there is something we don’t fully understand. ChatGPT will summarize it and explain. These tools are good for rewriting, taking text and turning it into something else that is easily understood, even with a different professional tone. Try it yourself the next time you post a book review on Amazon.
The beauty of working with AI is that it will rewrite as many times as we tell it to. The most important element of this is the quality of input and the type of input command from the user. Just like ads for a recent search term will start showing up on Google, AI will remember style of writing and commands from the user. Machine learning is an important tool in the field of AI because it enables machines to learn from data and improve their performance over time. By training algorithms on large datasets, machine learning can enable machines to recognize patterns, make predictions, and perform tasks with increasing accuracy. Overall, machine learning is a key component of AI, as it provides a means of teaching machines to learn and adapt in ways that are similar to how humans learn and adapt.
Accessibility of AI and Machine Learning
Machine learning and AI have become increasingly accessible to normal users in recent years, thanks to advancements in technology and the availability of user-friendly tools and platforms. Numerous online courses and tutorials are available on websites like Coursera and Udemy and require no prior coding or technical knowledge. There are also open-source libraries and frameworks, which are free to access, making it easier for normal users to experiment with machine learning algorithms and build their own AI applications. If so inclined you can see a couple at TensorFlow and PyTorch. As a disclaimer, I don’t use those tools as I really don’t need to spend the time to use them in my type of business, at least not yet.
Cloud-based AI services such as Amazon Web Services (AWS), Google Cloud and others have pre-built AI services and platforms. I have used AWS for a number of years for cloud storage, but it has many more capabilities than just storage. While some level of technical understanding is beneficial, the availability of user-friendly tools, educational resources and cloud-based services has made machine learning and AI more accessible to normal users. This is especially valuable as the new workplace will continue to use more and more AI for automation so it will be of great value to equip ourselves to use AI with accessible tools.
Ethical Issues
AI is open source and available for all at the basic level. Once you download the app, you possess the tools to use it. There will always be bad actors who have questionable motives and intent with nefarious purposes, yet there are also many using these tools with integrity, good intent and mission. For those who create intellectual property, if that content is only created with AI tools, that material can’t be copywritten. But if it’s instigated with an original idea from a creator, along with revisions from a creator, a copyright can be obtained.
Currently, there are many grey areas, but there are programs that can now discern if material is only created with AI. This will especially be important in our educational system with student’s essays and writings. A challenging area concerning ethical issues is in the political arena with impersonation and voice cloning. AI has been able to clone voices and even video very realistically. This can be extremely dangerous within a political landscape and we can be sure that it will show up in upcoming campaigns on all platforms. Using discernment and common sense will be necessary skills during bumpy political rides. Also, phishing techniques within realistic emails and videos deceive and extract users to give passwords and even life savings. Vigilance should be top-of-mind as we look out for all close family members and friends. (See book: Bad Code)
Opportunity
A person who’s skilled at AI has the potential to provide ten times the value as a non-skilled person. There will be job losses in certain areas that include repeatable tasks, just as what occurred in the Industrial Revolution over 150 years ago. We now have assembly lines for creating cars, but there are still individuals supervising the machines and inspecting for quality. In the same way, modern farms use large computerized machinery for automated tasks, cutting down on the number of manual workers. However, manual labor is still in high demand. Also, the opportunity for trades has never been higher as humans are still needed as welders, carpenters, electricians, plumbers and many more areas. Most of the trades some sort of tools for automation but there is usually always a human also involved in some manner.
Great opportunity is available if we understand the areas where we need to equip ourselves. Technology and AI is moving faster and faster, but there has never been a better time in history to have access to powerful tools for reinvention and change.
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- about ANGIE CALLEN
Christopher Penn is an IBM Watson Machine Learning Certified Professional, a Google Analytics Certified Professional, a Google Ads Certified Professional, a Google Digital Sales Certified Professional, and a Hubspot Inbound Certified Professional. He is the author of over two dozen marketing books including bestsellers such as AI for Marketers: A Primer and Introduction, Marketing White Belt: Basics for the Digital Marketer, Marketing Red Belt: Connecting With Your Creative Mind, and Marketing Blue Belt: From Data Zero to Marketing Hero, and Leading Innovation. He's also a six-time IBM Champion in IBM Data and AI, a Brand24 Top 100 Digital Marketer, an Onalytica Top 100 AI in Marketing influencer, and co-host of the award-winning Marketing Over Coffee marketing podcast.
A person who’s skilled at AI has the potential to provide ten times the value as a non-skilled person.
deborah johnson
Thought Leader, Keynote Speaker, Author
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