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How does AI actually work? What's the difference between machine learning and deep learning? Can AI really help pastors? We explore the answers to those questions right here.
We truly live in a time of innovation that, in a lot of ways, seems comparable to the science fiction we see in pop culture.
While we’ve yet to experience flying cars or sentient robots, the advancements of everyday technology, from self-driving cars to the smartphones in our pocket, are truly a milestone in the way technology was thought about a hundred years ago.
In the last couple of decades, and especially the last couple of years, you may have heard of a particular subject of interest in advanced technology... Whether you follow the news, are on social media, have an interest in tech trends, simply use a smartphone or even have a self-driving car, chances are you’ve encountered Artificial Intelligence (AI).
Artificial intelligence can tend to be a relatively hot-button issue with opinions ranging from the favorable views of AI’s practical efficiencies, to the less-than-favorable views on AI regulation and whether or not AI is discouraging critical thinking or creativity.
If you’ve ever heard or read any discussion, discourse or mention of AI and, like myself, thought:
1. “What exactly is AI?”
2. “And as a Christian, should I be skeptical of man-made intelligence?”
Then look no further, because in this blog I will be discussing how AI is defined, how it works and how it can even be a reliable tool for pastors.
To start with the basics, how exactly does one define Artificial Intelligence?
My initial reaction to artificial intelligence had originally been skewed by perhaps watching too many movies. If you’re worried about the likes of betrayal from a superintelligent computer named HAL or the revolt of humanoid robots, then I’m here to tell you that our current state of AI isn’t quite Stanley Kubrik’s 2001: a Space Odyssey nor the Will Smith led i, Robot.
According to Rockwell Anyoha of Harvard University, artificial intelligence is a concept that’s gone back as far as the 1950’s with british polymath Alan Turing’s notable paper Computing Machinery and Intelligence, where Turing “suggested that humans use available information as well as reason in order to solve problems and make decisions, so why can’t machines do the same thing?”
The development and advancement of AI has gone through a long history since then. From one of the leading AI developers themselves, IBM explains that:
“At its simplest form, artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms which seek to create expert systems which make predictions or classifications based on input data.”
To put this in layman terms, artificial intelligence allows machines the ability to problem solve through computer science and data. Still, you might be asking, “What do machine learning and deep learning even mean?” Well…
According to Coursera, machine learning “is a subset of AI” and is the “study of computer systems that learn and adapt automatically from experience, without being explicitly programmed.”
Basically, the way this works is a computer scientist programs algorithms, which in a sense are a “set of rules” for the machine to follow. A computer scientist can then “train” the machine to problem solve and make decisions “by feeding it large amounts of data.”
The machine is then able to carry out tasks and decision making by using algorithms to analyze and draw logical conclusions from datasets (in other words, a collection of data). The more data a machine is fed, the better the machine’s decision making.
The way Spotify is able to make suggestions based on your music preferences, or how Netflix curates a personalized “Top Picks For you” category are products of machine learning.
Coursera defines deep learning as the next evolution in machine learning, explaining that it’s “a machine learning technique that layers algorithms and computing units—or neurons—into what is called an artificial neural network.”
When a machine learning algorithm fails, correction is required from a human to create a more efficient algorithm. Rather, deep learning algorithms are able to self-improve their decision-making outcomes through repetition, thus eliminating the need for human intervention.
Interestingly, the model of deep learning is more akin to the neural structure of the human brain and requires big data sets, whereas machine learning is able to learn from relatively small datasets. The way this works is that a nonlinear input of diverse data crosses a web of “interconnected algorithms,” causing a machine to process information very similarly to how our brains do the same.
ChatGPT uses deep learning to write speech in a similar way that humans communicate, giving it a versatile range of skills from generating essays to answering conversational questions.
The trend of “AI artwork” also relies on deep learning.
Depending on what source you read, there can be anywhere between four to seven types of Artificial Intelligence. To save some time for you and I, IBM makes two very simple distinctions:
Also known as “Narrow AI,” Weak AI is what’s commonly used in our world today. While this form of AI is a very powerful tool, the terms “weak” and “narrow” are used to describe its limited capability of performing trained, specific tasks. Whether it’s asking Apple’s Siri about the weather, filtering spam emails or even prompting ChatGPT to write a report, these decision-making machines are all a product of Weak AI.
While Weak AI is used regularly in today’s world, Strong AI is theoretical and still in the process of being researched. This form of AI would not only be equal to human intelligence, but also have “self-aware consciousness” with the abilities to “solve problems, learn, and plan for the future,” and could even have the capacity to “surpass the intelligence and ability of the human brain.” In this case: yes, HAL from 2001. Yikes.
As you can probably tell by now, artificial intelligence is no stranger to modern technology. AI is used in many different industries, such as:
Artificial intelligence can even be used for assistance in ministry.
Through deep learning mechanics, pastors now have access to AI tools to help streamline the process of sermon preparation.
AI helps by not creating the sermon itself, but rather creating sermon outlines, finding relevant verses or stories in the Bible for a given topic, conducting research, developing character studies and even coming up with modern day examples of biblical topics.
With the advancement of artificial intelligence, there can be understandable reason for skepticism. As a pastor it’s important to uphold God’s word, listen to what God is speaking and to guide the church accordingly. While certain concepts of AI may raise alarm when it comes to the relationship between God and humanity (i.e. the theory of “Strong AI”), it’s important to have an understanding of how AI works, and discerning where to draw the line.
While artificial intelligence is a complicated concept with a versatility of uses in modern technology, it’s worth having a basic understanding of what it is, how it’s used and how it can help you. Ultimately AI shouldn’t be used to replace the personal relationship and understanding of God, though it can certainly be helpful in creating an efficient workflow for church leaders.
