For Christians, the ethics of artificial intelligence is more than a technical debate—it’s a moral conversation that touches on how we reflect God’s character and navigate this rapidly changing world.

Let’s explore the ethics of AI from a biblical perspective, considering how we can engage with this technology responsibly and faithfully.

The Age of AI and Ethics

Artificial intelligence is reshaping how we work, live, and connect, from the algorithms that recommend what show to watch next on your favorite streaming platform to systems that help doctors diagnose diseases.

But just what is AI?

At its core, AI is the ability of machines to simulate thought processes—to think like a human. These systems analyze data, recognize patterns, and make decisions in ways that once seemed impossible for a machine.

Impressive, yes. But AI is also profoundly influential.

It raises questions not just about what it can do but also what it should do. And that’s where the conversation shifts from technology to morality.

What Is Ethics?

Ethics might seem like a big, philosophical word, but at its heart, it’s simply the study of moral right and wrong.

Ethics gives us a framework for deciding how to live, work, and interact with one another. It asks questions like: What’s the right thing to do in a given situation? How do we balance our needs with the needs of others?

Ethics isn’t just about avoiding harm; it’s about pursuing good.

Ethics take on an even more profound significance when applied to something as transformative as AI. 

Expanding beyond personal decisions, ideas abound about how these powerful systems influence societies, communities, and individuals.

What Are Christian Ethics?

Christian ethics aren’t just a list of dos and don’ts scribbled in the margins of our lives; they reflect God’s unchanging character and his design for how we’re meant to live.

Grounded in Scripture, Christian ethics remind us that every decision, no matter how small, is an opportunity to demonstrate our faith and show the world who God is.

When Jesus preached the Sermon on the Mount, he wasn’t merely giving a moral checklist; he was inviting us into a life that reflects the heart of God.

“Blessed are the merciful, for they will be shown mercy. Blessed are the pure in heart, for they will see God” (Matthew 5:7–8). These aren’t just aspirations—they’re blueprints for how we’re called to live, transforming our ethics into a living testimony of God’s grace. Christian ethics call us to pursue righteousness, to love our neighbor as ourselves, and to shine his light in a dark world. We are to develop godly virtues with the help and empowerment of the Holy Spirit. Thus, we cannot be fully moral on our own power. We were designed to partner with God to live moral and upright lives.

Christian ethics urge us to move beyond the superficial and step into a kingdom perspective. They remind us that every breakthrough, every advancement, and every opportunity is a chance to echo the words of Jesus: “Whatever you did for one of the least of these brothers and sisters of mine, you did for me” (Matthew 25:40).

Whether we’re innovating, creating, or leading, our mission is clear: to let God’s love and truth shape how we engage with the world, leaving it brighter and better for his glory.

What Is AI Ethics?

AI ethics is the application of moral principles to the creation and use of AI systems. It’s a conversation about ensuring fairness, accountability, and transparency in these systems’ operations.

AI ethics ask essential questions, such as how we prevent bias in AI systems. How do we protect privacy in a world where machines collect more and more data? Who is responsible when AI makes a mistake?

These aren’t just technical issues but moral dilemmas that demand thoughtful, principled investigation and answers.

For Christians, AI ethics represent an opportunity to lead. By grounding our approach in God’s truth, we can ensure that this powerful technology is used not to harm but to help—not to divide but to draw us closer to his purpose for humanity.

The Ethics of AI Conversation

AI holds immense potential to transform our lives, yet its rapid evolution presents profound ethical dilemmas that call for thoughtful, faith-centered reflection.

These issues intersect with Christian values, calling us to steward this powerful tool in ways that honor God and serve humanity. How we address these challenges is not just a question of technological innovation—it’s a matter of moral integrity.

Ethical Issues of Artificial Intelligence

Many AI systems operate as “black boxes,” making decisions without explanation. This lack of transparency and accountability can foster mistrust and create fertile ground for misuse.

Scripture calls us to “walk in the light” (1 John 1:7), emphasizing integrity and accountability. Transparency in AI is a moral obligation that builds trust and ensures responsible stewardship.

Bias in AI Systems

Despite their promise of objectivity, AI systems often inherit the unjustified biases embedded in the data on which they are trained.

For instance, an AI-powered hiring tool might inadvertently favor specific demographics, perpetuating inequality instead of eliminating it.

As Christians, we are called “to act justly and to love mercy and to walk humbly with your God” (Micah 6:8). Justice is not optional—it’s a command. Fixing unjustified bias in AI requires humility and accountability, ensuring that technology reflects fairness and equity rather than deepening societal challenges.

Privacy & Surveillance Driven by AI Technology

Privacy and surveillance present another significant complication.

AI relies heavily on vast amounts of data to function effectively, but this dependence raises concerns about how that data is collected, stored, and used. Tools designed to protect can easily be misused as instruments of control, infringing on personal freedoms and dignity.

Christian ethics reminds us that every individual is made in the image of God (Genesis 1:27), and their relevant and proper privacy must be respected as an extension of their inherent worth. Safeguarding privacy isn’t just a legal issue; it’s a moral obligation to protect the sacredness of human life in a world increasingly driven by data.

Ethical Concerns of AI and the Human Cost

The promise of artificial intelligence is dazzling—efficiency, automation, streamlined processes, and endless possibilities for growth. Make no mistake, industries are being transformed before our very eyes.

Yet, the glow of progress has a shadow. Every breakthrough carries a cost—displaced workers, disrupted livelihoods, and the subtle erosion of human dignity.

As followers of Christ, we’re called to look beyond the data and see the people impacted by these changes. Jesus’s teaching to “love your neighbor as yourself” (Matthew 22:39) compels us to respond with compassion and advocacy.

Faithful stewardship means balancing innovation with care, ensuring that progress does not come at the expense of human worth. Technology must serve humanity, preserving dignity rather than sacrificing it for efficiency.

With AI’s rise comes great potential but also great risk.

Few concerns are more sobering than the weaponization of AI, where autonomous systems make life-and-death decisions without proper moral guidance. Such uses stray far from God’s vision of peace. Jesus declared, “They must not slander anyone, but be peaceable, gentle, showing complete courtesy to all people.” (Titus 3:2). Technology should reflect the Creator’s heart, protecting life rather than threatening it.

AI’s ability to influence behavior also raises additional ethical concerns. Algorithms shape our thoughts and choices, often prioritizing profit over truth. Christian ethics calls us to think about “whatever is true, whatever is noble, and whatever is admirable” (Philippians 4:8), reminding us to design systems that uplift and inform, not deceive or manipulate.

AI also risks undermining the relationships that define us.

From robots offering companionship to automated interactions replacing human touch, technology sometimes edges out the personal connections God designed us to share. The Bible urges us to “spur one another on toward love and good deeds” (Hebrews 10:24).

As Christians, we must guide AI to deepen connections, not replace them. We must work to ensure that love, empathy, and the gift of presence remain at the heart of our communities.

AI Ethical Dilemma Examples

Artificial intelligence doesn’t exist in a vacuum of theoretical possibilities—it’s woven into the very fabric of our daily lives, often in ways we scarcely realize. These dilemmas are not abstract; they touch on real issues that affect real people.

Consider the hiring algorithm designed to streamline recruitment. Its efficiency is appealing, but what happens if it unintentionally excludes certain demographics, perpetuating systemic AI bias?

Or was the surveillance system created to enhance safety? What happens when it oversteps its bounds, infringing on personal freedoms and turning protection into control?

Autonomous weapons powered by AI make life-and-death decisions without human oversight. Who bears responsibility for their actions? And then, there are algorithms designed to manipulate user behavior, exploiting vulnerabilities for profit rather than serving the common good.

Each scenario highlights the urgent need for a Christ-centered approach to technology.

As stewards of God’s creation, we’re called to approach AI cautiously, ensuring it aligns with his principles of justice, compassion, and integrity.

These are not just challenges for engineers and policymakers; they are moral questions that demand the involvement of people of faith willing to engage with humility and courage.

Can AI Be Ethical?

The question, Can AI be ethical? is about more than technology—it’s about the people who design, implement, and steward it.

AI is neither good nor evil; it’s a tool shaped by the values and intentions of those who create it.

Its potential for harm is undeniable, but so is its potential to serve as an instrument of hope and healing. The answer lies in how we choose to use it.

Christian ethics remind us that our ultimate accountability is to God.

When we approach AI with humility, wisdom, and a heart aligned with his values, we can ensure it reflects his love and light.

This means prioritizing justice over convenience. Transparency over secrecy. Human dignity over profit. It means asking what AI can do and what it should do and designing it to serve others with integrity and compassion.

Christian Ethics in the Age of AI

AI offers us a remarkable opportunity to reflect God’s character in our innovation. By holding ourselves to his standard, we can create technology that uplifts human nature rather than exploits, unites rather than divides, and serves rather than dominates. The ethics of AI conversation invites us to think deeply and act responsibly, aligning our actions with God’s eternal truth. Christians should use AI while being mindful and strategic to develop virtues in one’s character.

As Christians, we’re called to be a light in the world, even in spaces dominated by algorithms and code. We can approach the development and use of artificial intelligence as a spiritual calling, ensuring it glorifies God and serves humanity with justice, mercy, and love.

Advocating for Biblically Ethical AI

Practical steps start with advocating for biblically informed fairness in AI, ensuring everyone has equal access to its benefits, and promoting transparency in its use. Above all, Christians should see AI as a tool to uplift humanity, not diminish it.

The Bible reminds us that every person is made in God’s image (Genesis 1:27). This truth must shape how we approach AI’s ethical challenges. If AI devalues human work, disrupts relationships, or leads to practices that strip away dignity, we cannot stay silent.

As followers of Christ, we are called to push back—prioritizing human worth and God’s design over the lure of technological convenience.

3 Guiding Truths for Navigating AI Ethics

As we step into the uncharted waters of artificial intelligence and its many ethical dilemmas, it’s easy to feel adrift. The questions are big, and the challenges are complex.

But as Christians, we have a steady anchor—the eternal truths of Scripture. These truths remind us that while technology may seem daunting, our faith doesn’t rest on human ingenuity or innovation. It rests firmly on the unchanging character of God.

When the path is unclear, we can look to his Word for guidance, knowing his wisdom, sovereignty, and love are constant. AI may be new, but the principles that guide us are as timeless as the God we serve.

Let’s explore three truths that steady our hearts and light our way as we navigate the AI ethical crossroads.

1. God’s Sovereignty Over All Creation (Colossians 1:16–17)

AI may feel overwhelming, but let us not forget that it is part of the creation over which God reigns supreme.

Nothing, not even the most advanced algorithm, escapes his control. He is the Creator of all things—visible and invisible—and he holds everything together in his sovereign hands.

When the ethical questions surrounding AI seem too large to handle, we can rest in the knowledge that God’s sovereignty has not been shaken. Every innovation, every decision, and every moment is under his watchful eye.

His plan is good, his wisdom is infinite, and his authority remains unchallenged.

2. Human Worth is Rooted in God (Psalm 139:13–14)

In a world increasingly measured by efficiency, productivity, and comparison, it’s easy to feel small next to machines that seem to outperform us.

But Scripture reminds us that our worth isn’t tied to what we can do—it’s rooted in who we are: creations of a loving God. He has prepared us for an opportunity to be his ambassadors and perform good works—even with AI. “For we are God’s handiwork, created in Christ Jesus to do good works, which God prepared in advance for us to do” (Ephesians 2:10).

We are fearfully and wonderfully made, woven together with care and purpose by the Creator of the universe. AI may calculate faster, analyze better, and execute tasks precisely, but it will never hold the worth of a soul redeemed by Christ.

Our value is not something a machine can replicate or replace. It is infinite, eternal, and grounded in the truth that we’re made in the image of God.

3. God’s Wisdom Guides Our Decisions (Proverbs 3:5–6)

The ethical concerns of AI often feel like navigating a maze with no clear end in sight. But as Christians, we’re not left to figure it out alone. God’s wisdom is available to us, and his guidance is unfailing.

When we trust him and submit our decisions to his will, he promises to make our paths straight—even through the tangle of ethics in AI.

Leaning on God’s wisdom means approaching these challenges prayerfully, seeking his counsel through Scripture, and listening for his voice in our decisions. It means trusting he’ll illuminate the way, even when the road is unclear.

Approaching Artificial Intelligence with Faith and Wisdom

Biblical truths remind us that God’s sovereignty, the inherent worth he has placed on humanity, and his unfailing wisdom are constants in a world of rapid change.

So, we can face the ethical concerns of AI with confidence—not in our abilities, but in his promises. He is the same yesterday, today, and forever. His hand guides us, his heart cares for us, and his truth anchors us in every storm.

The age of AI is here. The question is, how will we, as Christians, rise to meet it?

Will we lean into God’s wisdom, using this technology for his glory? Or will we let the world’s standards dictate its use? The choice is ours, and it’s a choice that matters.

As we engage with these questions, we can trust in the God who sees, knows, and holds all things together.

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ANL has seen rapid change in recent years. When I was a child incandescent bulbs accounted for all ANL. During my teenage years, mercury vapor lamps began to supplant incandescent bulbs for the simple reason that mercury vapor lamps delivered more lighting at a lower energy expenditure. Consequently, that transition dramatically increased ANL not only in Canada and the United States but all over the world.

Mercury vapor lighting emits predominantly at blue wavelengths. However, it’s now known that blue nighttime lighting suppresses melatonin.¹ The suppression of melatonin (the hormone of darkness) disrupts sleep patterns in both humans and animals.

Low-pressure sodium lamps brought about the next big transition in ANL. These sodium lamps produce more light per unit of energy invested than mercury vapor lamps. Hence, they increased ANL.

Extent of LED Lighting
In a paper published in a recent issue of Science Advances, a team of five astrophysicists and environmentalists led by Alejandro Sánchez de Miguel produced the first composite ANL full-color maps of Europe using imagery obtained from the International Space Station (ISS). The ISS database of ANL images of Europe from 2003 to the present now exceeds 1.25 million images.

Sánchez de Miguel’s team pointed out just how dramatically LED (light-emitting diode) lights have increased ANL in Europe and likely around the world.² LED lighting yields, by far, the most dramatic increase in lighting per unit of energy invested of any technological development over the past century. Figure 1 shows ANL in Madrid before the introduction of LED lighting (2012) compared to ANL after the beginning of LED lighting installation (2017). Figure 2 shows ANL in London before LED lighting (2012) and after the beginning of LED lighting installation (2020).

Though the differences in the before and after images shown in figures 1 and 2 are dramatic, the conversion to LED street lighting is not yet complete in Madrid and London. For the right-hand part of figure 1, just 56% of public street lighting was converted from sodium high- and low-pressure lamps to LED. For the right-hand part of figure 2, 51% of public street lighting was LED. Both Madrid and London and virtually all large European cities are committed to making 100% of public street lighting LED.

Conversion to LED street lighting illustrates what’s called Jevon’s paradox. This paradox states that increases in power efficiency in outdoor lighting combined with lower economic cost drive up the demand for more lighting. Hence, any efficiency gains in ANL are counteracted by increased consumption of ANL. Therefore, Europe and likely the rest of the world have witnessed an exponential increase in ANL.

Biological Consequences
Humans, animals, and plants are impacted in different ways by the intensity and color of ANL. Like mercury vapor lamps, LED lights emit strongly at blue wavelengths. Hence, LED nighttime lighting suppresses melatonin production in humans and vertebrate animals to an exponentially unprecedented degree.³ This suppression not only reduces the duration and quality of sleep, it disrupts circadian cycles and temporal organization in mammals, birds, reptiles, and plants. For birds and mammals, it disrupts the operation of nearly every internal organ. As I described in a previous article, a recent scientific study has established that sleep loss in humans substantially reduces acts of altruism.⁴

The flocking of moths to bright outdoor nighttime lights is an example of a phototaxic response. Moths are joined by many other insect species in their strong attraction to ANL and in their vigorous flying activity adjacent to ANL. Scientific studies have established that ANL alters the DNA-to-RNA ratios in insects.⁵ Other studies show that ANL has reduced insect populations.⁶ Thus, there is the real risk that LED ANL could soon cause catastrophic declines in some insect populations.

In an article I wrote two years ago, I described studies that had shown that nocturnal moonlight and phases of the moon regulate coral spawning. I also explained that the recent introduction of LED lighting at certain tropical beach resorts had caused the failure rate of spawning coral colonies to rise from 6–20% to 93–100%.⁷ Similar to the risk to insects, LED lighting adjacent to beaches could eradicate coral reefs near these beaches and all the marine life dependent upon them.

Bats comprise one-quarter of all mammal species. Several studies have demonstrated that ANL strongly disturbs the behavior of bats in foraging for food, disrupts their sociability and flight routes, and limits their ability to disperse seeds.⁸ Since nearly all bats are nocturnal, the expected increase in ANL during the next decade could decimate their population levels, possibly endanger many bat species, and exacerbate landscape recovery.

One of the most dramatic and noticeable impacts of ANL is the decreased visibility for humans and animals to see stars. Analysis of data from satellites established that in 2014 more than 80% of the world’s population and more than 99% of people living in the United States and Europe experience noticeably reduced ability to see stars.⁹ The installation of LED lighting in many major cities of the world has kept people living in those cities from being able to see any stars at all.

Many animal species depend on the visibility of stars for navigation.¹⁰ Migratory birds, itinerant seals, and even some insect species use the stars and/or the Milky Way for navigation.

For humans, not seeing the starry sky deadens our sense of nature’s wonder. It can stymie contemplation of our place and purpose in the universe. Psalm 19:1 and 97:6 state that the heavens declare the glory and righteousness of God. Some places are so light-polluted that the heavens are not declaring anything at all. It’s no coincidence that the rise in the number of people professing to be atheists, agnostics, and nones (no religious affiliation) correlates with the intensity and ubiquity of ANL.

Managing Resources Wisely
As noted earlier, the benefits of ANL can’t be denied. However, the exponential increase in ANL we’ve experienced over the past several years as a result of LED lighting installation has produced deleterious consequences for plants, animals, and humans that can no longer be denied or ignored.

As I explained previously, natural night lighting, namely light from the Moon, planets, and stars is optimally designed to benefit Earth’s life.¹¹ Acknowledgment of this optimal design of night lighting may help the peoples of the world recognize that ANL is now upsetting God’s perfect design.

For people living in large cities, God’s glory and righteousness revealed in the heavens are barely noticeable to the unaided eye. However, telescopes are a lot more affordable today than they were before the availability of mercury vapor and LED outdoor lighting. I have consistently seen non-Christians drawn to acknowledge our Creator-God when they look through my telescope at galaxies, globular clusters, and nebulae. During the past few weeks, I have seen a similar response to people staring at the spectacular images taken by the James Webb Space Telescope.

In Genesis 1 God assigns to humanity the responsibility to manage Earth’s resources for the benefit of humans and of all other life on Earth. The benefits we gain from ANL do not require either their current intensity or ubiquity. It’s time to optimize ANL levels for the maximum benefit and health of humans, animals, and plants. Astronomers in particular, both professionals and amateurs, will be grateful.

Endnotes

1. Thomas W. Davies et al., “Artificial Light Pollution: Are Shifting Spectral Signatures Changing the Balance of Species Interactions?” Global Change Biology 19, no. 5 (May 2013): 1417–23, doi:10.1111/gcb.12166; Travis Longcore et al., “Rapid Assessment of Lamp Spectrum to Quantify Ecological Effects of Light at Night,” Journal of Experimental Zoology A. Ecological and Integrative Physiology 329, nos. 8–9 (October 2018): 511–21, doi:10.1002/jez.2184.
2. Alejandro Sánchez de Miguel et al., “Environmental Risks from Artificial Nighttime Lighting Widespread and Increasing across Europe,” Science Advances 8, no. 37 (September 14, 2022): id. eab16891, doi:10.1126/sciadv.abl6891.
3. Maja Grubisic et al., “Light Pollution, Circadian Photoreception, and Melatonin in Vertebrates,” Sustainability 11, no. 22 (September 14, 2019): id. 6400, doi:10.3390/su11226400.
4. Hugh Ross, “Sleep Loss and Altruism Decline,” Today’s New Reason to Believe (blog), Reasons to Believe, October 10, 2022, /explore/blogs/todays-new-reason-to-believe/sleep-loss-and-altruisim-decline.
5. D. Quintanilla-Ahumada et al., “Exposure to Artificial Light at Night (ALAN) Alters RNA:DNA Ratios in a Sandy Beach Coleopteran Insect,” Marine Pollution Bulletin 165 (April 2021): id. 112132, doi:10.1016/j.marpolbul.2021.112132.
6. Judith L. Kühne et al., “Impact of Different Wavelengths of Artificial Light at Night on Phototaxis in Aquatic Insects,” Integrative & Comparative Biology 61, no. 3 (September 2021): 1182–90, doi:10.1093/icb/icab149.
7. Hugh Ross, “Artificial Night Lighting May Cause Ecosystem Collapse,” Today’s New Reason to Believe (blog), Reasons to Believe, January 4, 2021, /adam-eve/tools-tech/artificial-night-lighting-may-cause-ecosystem-collapse.
8. Bo Luo et al., “Artificial Light Reduces Foraging Opportunities in Wild Least Horseshoe Bats,” Environmental Pollution 288 (November 1, 2019): id. 117765, doi:10.1016/j.envpol.2021.117765; Emma Louise Stone, Gareth Jones, and Stephen Harris, “Street Lighting Disturbs Commuting Bats,” Current Biology 19, no. 13 (July 2009): 1123–27, doi:10.1016/j.cub.2009.05.058; Daniel Lewanzik and Christian C. Voigt, “Artificial Light Puts Ecosystem Services of Frugivorous Bats at Risk,” Journal of Applied Ecology 51, no. 2 (April 2014): 388–94, doi:10.1111/1365-2664.12206; Alexis Laforge et al., “Reducing Light Pollution Improves Connectivity for Bats in Urban Landscapes,” Landscape Ecology 34 (April 15, 2019): 793–809, doi:10.1007/s10980-019-00803-0.
9. Fabio Falchi et al., “The New World Atlas of Artificial Night Sky Brightness,” Science Advances 2, no. 6 (June 10, 2016): id. 1600377, doi:10.1126/sciadv.1600377.
10. James J. Foster et al., “How Animals Follow the Stars,” Proceedings of the Royal Society B: Biological Sciences 285, no. 1871 (January 31, 2018): id. 20172322, doi:10.1098/rspb.2017.2322; Björn Mauck et al., “Harbour Seals (Phoca vitulina) Can Steer by the Stars,” Animal Cognition 11, no. 4 (October 2008): 715–18, doi:10.1007/s10071-008-0156-1; James J. Foster et al., “Stellar Performance: Mechanisms Underlying Milky Way Orientation in Dung Beetles,” Philosophical Transactions of the Royal Society B: Biological Sciences 372, no. 1717 (April 5, 2017): id. 20160079, doi:10.1098/rstb.2016.0079.
11. Hugh Ross, “Lunar Designs Optimize Life for Both Predators and Prey,” Today’s New Reason to Believe (blog) Reasons to Believe, November 20, 2017, /creation/universe/lunar-designs-optimize-life-for-both-predators-and-prey.

The post Is <em class="algolia-search-highlight">Artificial</em> Nighttime Lighting Too Much of a Good Thing? appeared first on Reasons to Believe.

I am thankful for having spent my career in AI, initially as a graduate student, and subsequently as a research scientist, professor, and entrepreneur. I am also grateful to have stimulating discussions today with the youngest generation of researchers and engineers about their coolest AI. There are no doubts in my mind that AI will continue to improve, and I look forward to hearing about more breakthroughs that will improve our lives.    

However, some imaginations about the future of AI are troubling, especially those raising theological questions. Does AI prove the nonexistence of God? Will AI empower humans to become gods? Can God survive AI? According to Professor Michael Keas, who specializes in the history of science, AI has become a futuristic myth to add fuel to the alleged warfare between science and religion.¹ This short article responds to these theological AI claims from a research perspective. It discusses how this future-oriented myth relates to a bigger framework of past-oriented myths on the so-called conflict between science and faith. First, let’s look at some theological AI claims.

ET-Enlightenment

Supporters of the ET-Enlightenment speculation claim that extraterrestrial life (ET) will be equipped with super-AI. Their idea is based on these assumptions: 

1. Life on Earth emerged through Darwinian unguided evolutionary processes.
2. Advanced life must have emerged in the universe through some similar evolutionary process.
3. Since human technology is too primitive to detect ET, we will be found by ET with superior AI. 

Assuming that unproven Darwinian evolution is true, nontheists extrapolate that superintelligent ET will come to Earth one day, bringing a superior spirituality from the heavens without God.

Artificial General Intelligence

With the recent AI successes, there is optimism that a general form of AI, or AGI, will soon surpass human intelligence. These optimists speculate that robots will replace humans, a new form of life will be birthed, and science will destroy religions. Some even imagine that AGI will function as gods.

Upgrading Humans

Extreme AGI optimism propels imaginations even further. Such optimists think that physical death has been reduced to a mere technical problem waiting for a technical solution. Some even imagine that AGI will upgrade humans into gods or that transhumanism will merge humans with machines, thus remaking humans in the image of their own higher ideals.

Realistic View of AI

As a teenager, I was inspired by science fiction, which led me to AI. From my perspective, science fiction (or sci-fi) is stimulating and inspiring. It may even shape the future of scientific research. However, some of these theological AI scenarios are not in the genre of sci-fi, or are perhaps hidden under the guise of sci-fi. There seems to be a common objective of putting science in direct conflict with religion.

How much scientific evidence is there behind these speculations? Renowned hands-on researchers call these speculations absurd and science fiction. Professor John Lennox observes that the amount of unjustified speculation claimed for AI is inversely proportional to the amount of actual hands-on work in AI that the claimant has done.² I tend to agree. An experienced hands-on scientist would know that AI today is merely extracting salient patterns from a huge dataset. 

While Darwinian evolution from a common ancestor is still an unproven concept, the idea that future superintelligent ET bringing superior spirituality appears to be purely speculative. The passion for developing AGI to surpass human intelligence has been in existence since the birth of AI over a half-century ago. However, scientists today still have no idea how to define some of the basic features of human intelligence, such as self-consciousness, humor, and love. There is still a major chasm between today’s AI and a primitive form of AGI, let alone of replacing humans, conquering death, or becoming gods. Ironically, in the process of denouncing theology, these scientific ideas are becoming a theology themselves.

Six Science-Faith Warfare Myths

Historians of science explain that there was little or no conflict between science and faith for many centuries since antiquity.^3,4 Yet this futuristic AI myth that portrays conflict is not exactly new. Over the last several centuries, the proliferation of past-oriented science myths has obscured and distorted the facts, resulting in a complex relationship between science and faith. Here are six major science-faith myths that have made their way into textbooks and popular culture.

Big Myth

The big myth describes a premodern belief that the universe was small. Modern science displaced this church-sanctioned belief with a vast cosmos. However, this description is false because premodern people believed that the universe was very big. Ptolemy taught two thousand years ago that the earth had the ratio of a point to the heavens. Biblical authors used the greatness of the universe to illustrate the glory of the almighty God (Psalm 19:1, 103:11).

Dark Myth

The dark myth describes the church suppressing the growth of science, causing Europe to descend into the Dark Ages between 500 AD and 1500 AD. However, this story is false. Beginning in the fourth or fifth century, church leaders encouraged the integration of science and faith and wrote that the study of science was a form of worship. Furthermore, the church financially and socially supported the invention of the university, thus stimulating the growth of science. Beginning in Bologna in 1088, over 50 universities were established in Europe by 1450. About 30% of the liberal arts curriculum was on science-related subjects.⁵

Flat Myth

The flat myth is a subset of the dark myth, specifically used to demonstrate: (a) the ignorance of the church, and (b) its suppression of intellectuals who challenged belief in a flat earth until Christopher Columbus proved Earth’s roundness in 1492. However, this story is untrue. Ancient and medieval scholars had many evidence-based reasons to believe in Earth’s roundness.

Bruno Myth

This myth posits that Bruno was burned alive as a martyr of science in Rome in 1600. While this form of punishment in history was cruel, historians clarify that: (a) Bruno was a philosopher with a very faulty understanding of science at the time, (b) his trial was much more philosophy versus religion than science versus religion,⁶ and (c) he was executed almost entirely for theological reasons, not scientific ones. About a third of astronomy textbooks today tell this highly misleading myth.⁷

Galileo Myth

This myth holds that the church tortured and imprisoned Galileo in 1633 for constructing his telescope and for his idea of Earth going around the Sun. However, according to historians, Galileo received great honor and respect from the church before and during his trial. Nevertheless, Galileo betrayed the pope, denied receiving a special injunction, and even lied about the aim of his book. Though the church finally disclosed documents to the public in the nineteenth century, this myth has been in textbooks for centuries.

Copernican Demotion Myth

As canonized in the Catholic Church, Copernicus agreed that God formed the cosmos for humanity’s sake, affirming the harmony of the Bible with astronomy. Published in 1543, his book argued for Earth going around the Sun, thereby providing the basis for Newton’s work a century later. However, beginning in the seventeenth century as part of an anti-Christian effort, Copernicus’s astronomy was falsely portrayed as demoting humans. According to Keas’s survey, over 70% of astronomy textbooks today continue with this Copernican demotion myth.

Toward a Science-Faith Harmony

Science and Christianity ought to be in harmony with each other. However, myths fabricated over the past several centuries depict them as being perpetually at odds. These myths are still being used today to position Christianity as irrational and at odds with science. Having spent my entire career on AI mostly as a non-Christian, I am shocked that AI is being hijacked to become the seventh warfare myth between science and faith.

Our creativity in making AI work so amazingly reflects that we are made in God’s image. We should thank God for giving us the wisdom to develop AI to improve our lives.

Endnotes

1. Michael Newton Keas, Unbelievable: 7 Myths about the History and Future of Science and Religion (Wilmington, DE: Intercollegiate Studies Institute, 2019).
2. John Lennox, 2084: Artificial Intelligence and the Future of Humanity (Grand Rapids, MI: Zondervan Reflective, 2020).
3. Keas, Unbelievable.
4. Gary B. Ferngren, Science and Religion: A Historical Introduction, 2nd ed. (Baltimore, MD: Johns Hopkins University Press, 2017).
5. Keas, Unbelievable.
6. Maurice A. Finocchiaro, “Philosophy Versus Religion and Science Versus Religion: The Trials of Bruno and Galileo,” in Giordano Bruno: Philosopher of the Renaissance, 1st ed., edited by Hilary Gatti (New York, NY: Routledge, 2017).
7. Keas, Unbelievable.

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Algorithm Bias

A classic example of AI bias is found in COMPAS (Correctional Offender Management Profiling for Alternative Sanctions), a software support tool that assesses the likelihood of a defendant becoming a recidivist, which issues a risk score between 1 and 10 to indicate the likelihood of rearrest if a prisoner is released. It turns out that algorithms that try to predict recidivism can be heavily influenced by historical arrest rates. And because African Americans have been unfairly targeted for arrest in the past, these algorithms may also unfairly target the same population.

But there are many less obvious examples, such as the fact that until recently Twitter would center white male faces in images at the expense of minority individuals in the same image.¹  These issues of bias in AI extend into many different domains, including healthcare (accurate diagnoses), employment (who gets the job), and finance (who receives a loan).

How AI Bias Works: A Simple Example

In order to understand how bias gets into AI systems, let’s consider a simple hypothetical example of how AI uses data. The data in this example is based on real tip data, but is not representative of either New York City or Illinois. Let’s say that a restaurant chain owner—we’ll call him Joe—is opening a new restaurant in New York City. Most of his current locations are in rural Illinois. Because rent for the building in NYC is expensive, he decides to include the tip in a customer’s bill and wants to be fair about the size of these tips.

Joe decides to hire a data scientist to use tip data from his other restaurants to set the tip value. The data scientist has done this before for other customers in NYC and explains to Joe how it works. By fitting a line (y = mx + b) to tip data where “y” is the tip amount and “x” is the meal cost, you can then attempt to predict future tips using that same line (“m” is the slope of the line and “b” is the y-intercept of a line). This is called linear regression and it’s one of the simplest machine learning algorithms—when you hear about AI, you are usually hearing about machine learning, which is a subfield of AI. In this case, as shown in figure 1, the data scientist shows that a line fit to tip data collected from other restaurants in NYC would predict a tip of $5.10 for a meal that cost $40.00.

The data scientist then uses a similar process on Joe’s tip data from rural Illinois. It turns out that folks didn’t tip as much in rural Illinois. If Joe uses the Illinois tip data, his servers will receive a $3.00 tip for a $40.00 meal rather than a $5.10 dollar tip (see figure 2). These lower tips would be unfair wages for Joe’s servers in NYC even though they were fair wages for his workers in rural Illinois.

Where did that “bias” against waiters in NYC come from? It came from the data. All AI algorithms are built using data, so inaccurate or biased data leads to inaccurate or biased models. Or, as is often said, “junk in, junk out.” In this case, the tip data from Illinois should not be used to calculate tips in NYC. But the same principle applies to any other discipline, whether facial recognition, criminal prosecution, recommender systems, or healthcare.

Figure 1: Example of Linear Regression on Hypothetical NYC Tip Data

Source: Sean Oesch

Figure 2: Difference between Model Based on Hypothetical Illinois Tip Data (Red) and NYC Tip Data (Blue)

Source: Sean Oesch

Fixing Bias in AI Is Nontrivial and Doesn’t Fix Human Bias

There are several reasons why fixing bias in AI is a difficult problem:

1. Sometimes the data needed to create an unbiased system is simply not available so researchers encounter an ethical dilemma. Should we use a somewhat biased dataset or nothing at all?
2. Bias in AI systems can be difficult to identify until it shows up, especially when algorithms are trained on datasets so large that no human can effectively evaluate them for bias. This problem is more pronounced in fields such as natural language processing where massive bodies of text scraped from the Internet may be used to train models.
3. A model that is less biased can still be misused by biased humans. For example, China may have used facial recognition technology to target and detain the Uighur population in internment camps. In such cases, better facial recognition models hardly benefit the minority.
4. These observations lead to two significant questions worth mulling over. First, is AI always the right solution? We assume we should fix bias in AI, but maybe we shouldn’t be collecting and harnessing massive amounts of data in the first place.² AI is a powerful tool and it is worth considering when and how it should or should not be used. Secondly, how do we address the issue of bias in the human heart? Olga Russakovsky, a professor of computer science at Princeton, notes that, “Debiasing humans is harder than debiasing AI systems.”³ And this is really the crux of the problem: fixing bias in an algorithm doesn’t lead to correcting bias in society.

Christ Offers a Path to Addressing Bias in the Human Heart

It would be simplistic to say that believing the Christian message of all people being made in God’s image and equally in need of salvation fixes bias in the human heart. Setting the issue of hypocrisy aside, even committed followers of Jesus struggle with bias. One way to combat such bias is to admit our faults and seek the humility to listen across gender, racial, political, and theological divides—allowing others to convict and correct us when we go astray. Christ offers us this path to address the bias in our own hearts. There is no quick fix for human bias, but what Jesus gives us is the power to love and learn from those who are different than us and the motivation to make it happen.

Endnotes

1. Andrea Kulkarni, “Bias in AI and Machine Learning: Sources and Solutions,” Lexablog, Lexalytics, June 26, 2021, lexalytics.com/lexablog/bias-in-ai-machine-learning.
2. Julia Powles, “The Seductive Diversion of ‘Solving’ Bias in Artificial Intelligence,” Medium, OneZero, December 7, 2018, onezero.medium.com/the-seductive-diversion-of-solving-bias-in-artificial-intelligence-890df5e5ef53.
3. Will Knight, “AI Is Biased. Here’s How Scientists Are Trying to Fix It,” Wired (December 19, 2019), https://www.wired.com/story/ai-biased-how-scientists-trying-fix/.

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Having devoted my entire career to AI, starting as a graduate student in the 1980s, I am encouraged and exhilarated by what AI can do today. It has achieved widespread success in multiple applications, ranging from social marketing and face recognition to language translation and autonomous driving. AI has performed well beyond predictions made by many AI researchers as recently as one or two decades ago. As the research continues, AI will undoubtedly continue to make our lives better through technological breakthroughs that researchers have been dreaming of for decades.

However, some of the recent speculations and predictions about AI are puzzling, especially those that appear to raise theological questions. Does AI disprove the existence and necessity of an intelligent God? This short article answers this important question by focusing on a fundamental question: Is there any intelligence in AI? Perhaps a historical roadmap on AI will shed some light.

Births of Artificial Intelligence and Neural Networks

Over a half-century ago, two major academic disciplines emerged with the objective of making intelligent machines. These disciplines were artificial intelligence and neural networks (NN). They took on drastically different approaches. AI was spawned by the computer science community and it focused on symbolic representations and processing. NN was proposed by engineering researchers and it concentrated on numerical representations and computations. In 1969, Marvin Minsky and Seymour Papert, two of the early fathers of AI at the Massachusetts Institute of Technology (MIT), wrote a book carefully explaining what they saw as NN’s severe limitations.¹ Consequently, research on NN stopped for about a decade.

Resurgence of Neural Networks

However, in the 1980s, there was a resurgence of interest in neural networks.² A new mathematical formulation was proposed, leading to optimism that NN could solve many more problems than had been thought by people like Minsky and Papert. This new mathematical solution reignited the longtime debate: which technology would be more powerful? The AI community argued that there was too much “black magic” inside NN. They said that the way NN solved problems resembled neither human intelligence nor artificial intelligence. The NN community, however, argued that the interconnections inside NN resembled, at least by appearance, the physiology of neurons in the human brain. They claimed that with sufficient learning examples, interconnections, and computer processing power, NN would “learn” to solve many problems. As we now know, this claim turns out to be correct.

Alien in Artificial Intelligence

I found myself feeling like an alien when I was a PhD student in Tech Square, a building full of world-renowned professors, scientists, researchers, graduate, and undergraduate students from the MIT Artificial Intelligence Laboratory and the MIT Laboratory for Computer Science (both laboratories have now merged into the MIT Computer Science and Artificial Intelligence Laboratory, or CSAIL). I was frustrated by AI approaches that required tremendous handcrafting of rules and heuristics. NN fascinated me because of its formal mathematical framework to solve problems. I became one of the first few researchers in the world to do a PhD thesis on how to use NN and pattern recognition techniques for speech recognition. At the time, I found only two kinds of people among my AI friends: (a) the majority who considered NN as a bag of tricks, and (b) the minority who remained silent about NN.

Statistical Pattern Recognition

The debate between the AI and NN communities was not new. For decades, mathematicians and engineers had been working on pattern recognition (PR) to solve problems. A new statistical PR approach, called hidden Markov modeling (HMM), became mainstream technology for speech recognition.³ This PR community believed in the vigor of mathematical frameworks and argued that AI was too heuristic and labor-intensive. And they also rejected NN because (a) it lacked a tractable mathematical formulation, and (b) researchers had no idea what was going on inside the NN.

The Melting Pot

Fast forward to the 1990s and the 2000s, and the three disciplines of AI, NN, and PR were starting to merge slowly. New editions of PR textbooks began to add new chapters on NN and HMM.⁴ Similarly, AI textbooks started to teach about NN, HMM, and other PR techniques (in contrast to earlier editions).^5,6 Within the AI community today, many of these NN and PR techniques now reside under the umbrella of machine learning. From an academic perspective, it is awesome when researchers learn to reconcile their differences. Their cooperation allows the disciplines to merge, thereby pushing technology forward faster than ever before.

Many advances today ranging from face recognition and natural language to autonomous machines and medical diagnosis have been hailed as AI successes. However, thanks to today’s much faster computer hardware with significantly higher memory capacity, most, if not all, of these great successes are based on NN, whose fundamental concept has remained unchanged since its resurgence in the 1980s. For decades, the AI community did not consider NN as anything intelligent, but NN has now become the keystone of AI.

Where Is the Intelligence?

This melting pot of AI, NN, and PR could have been named anything, although “artificial intelligence” garners attention. AI includes other sophisticated terms such as deep learning and neural networks, but the name artificial intelligence captures the imagination of a continuum of communities: researchers, developers, managers, marketers, media, sponsors, fiction writers, and the public. If a different name had been chosen, this melting pot probably would not have drawn as much attention and controversy as it does today. Each group in this continuum seems to have a different perspective on AI. From my observations, the farther away the group is from the research, the more speculative (both optimistic and pessimistic) it becomes. But is “intelligence” a good descriptor for this melting pot? I don’t think so.

Technologists and engineers have developed numerous automatic machines over the past century. Automobiles run faster than humans. Computers add numbers faster than humans. Airplanes fly. These technologies make our lives better. Yet, they have no chance of replacing humanity. They are merely tools and do not cause any issues with the Christian faith other than how they are used.

Why would this AI melting pot be any different? Successful AI today is the culmination of decades of research in a vast spectrum of scientific, technological, engineering, and mathematical disciplines. And in my view, the NN in AI is not artificial or intelligent. It is real techno-engineering. Humans have designed, developed, and refined the technology at every step. As is the case with any technology, our creativity in this melting pot is a reflection of God’s image. The intelligence lies in human agents who have been charged with using our minds and creativity to serve humanity.

Endnotes

1. Marvin Minsky and Seymour A. Papert, Perceptrons: An Introduction to Computational Geometry, expanded ed. (Cambridge, MA: MIT Press, 2017).
2. David E. Rumelhart, James L. McClelland, and the PDP Research Group, Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Cambridge, MA: MIT Press, 1987).
3. Lalit R. Bahl, Frederick Jelinek, and Robert L. Mercer, “A Maximum Likelihood Approach to Continuous Speech Recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence 5, no. 2 (March 1983): 179–190, doi:10.1109/TPAMI.1983.4767370.
4. Richard O. Duda, Peter E. Hart, and David G. Stork, Pattern Classification, 2nd ed. (Hoboken, NJ: John Wiley & Sons, 2000).
5. Patrick Henry Winston, Artificial Intelligence, 3rd ed. (Boston, MA: Addison-Wesley, 1992);
6. Nils J. Nilsson, The Quest for Artificial Intelligence: A History of Ideas and Achievements (Cambridge, UK: Cambridge University Press, 2009).

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John Lennox started the workshop with an overview of AI. His talk discussed the difference between narrow AI and general AI. Narrow AI learns to do a specific task or group of tasks where general AI has the capacity to learn across a broad spectrum of fields or skills. Although the latter seems relegated to the distant future, the former already exists and is becoming pervasive. As narrow AI continues to grow, we must recognize that the technology brings potential for good, but also harm. One key takeaway from Lennox’s session is the notion that many people are looking to AI to save humans from the perils that plague us, including death. However, Lennox notes that salvation has already been accomplished by Jesus Christ’s death and resurrection.

Next, Jason Thacker spoke in his area of specialty, the ethical concerns surrounding technology. And AI certainly raises a plethora of them. The pursuit of general AI raises the question of what it means to be human—which Scripture answers directly by stating that we alone are the bearers of God’s image (Genesis 1:26–27). A second thing to consider as we pursue narrow AI is how to use it. We’ll be able to do facial recognition, automate various jobs, and develop autonomous weaponry. Although AI is a powerful tool, we can choose to use it for good or evil. Thacker wrestles with this question in the context of our postmodern society where ethics are difficult to determine and seem to vary from person to person. 

J. P. Moreland concluded the workshop by exploring the nature of intelligence and consciousness. The terms “weak AI” and “strong AI” are often used as synonyms for narrow and general AI. Moreland highlights one subtle but important difference between strong and general AI. Where general AI refers to an AI that has the capacity to learn across a broad spectrum of fields or skills, strong AI possesses an awareness of its ability to learn rather than just the ability to mimic human learning. Moreland then proceeds to provide a philosophical framework for understanding strong AI dubbed “machine functionalism.” At the basis of any naturalistic philosophy of mind or intelligence, machine functionalism holds that consciousness ultimately reduces to some arrangement of matter and the interactions between that matter. As a consequence, machine functionalism will inevitably diminish our view of consciousness.

Each session consists of an overview talk, followed by two panelists asking questions raised during the talk. Overall, the workshop provides a broad framework Christians can use to engage this challenging and exciting area of research. In my assessment, the pursuit of AI is inevitable. More importantly, if we are to use this powerful tool for good while mitigating the potential harm, we need to demonstrate the truthfulness of Christianity and lead the way in providing ethical guidance for all.

Resources

• What Is Intelligence and Can Humans Create It?, session 1 with John Lennox; see Lennox’s book, 2084.
• Ethics in the Age of AI: Defining and Pursuing the Good for Our Good, session 2 with Jason Thacker; see Thacker’s book, The Age of AI.
• Artificial Intelligence, Consciousness, and Human Intelligence, session 3 with J. P. Moreland; see Moreland’s book, The Soul.

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