The Coming Wave Summary

Will the technologies of the future save us or undo us? The answer lies in how we wield the tools we’ve created.

1. A New Wave of Technology

Technological advances are reshaping society as artificial intelligence and genetic engineering surge into daily life. These tools promise to revolutionize how we work, live, and interact, but they also bring risks that cannot be ignored. AI already powers tools like speech-to-text software, language translation, and autonomous driving, while genetic engineering is progressing toward advanced treatments and disease-resistant crops.

The new technologies evolve by merging capabilities. Smartphones, for instance, now combine GPS, cameras, and machine learning. AI and genetic tools offer similar leaps, but history has shown technology often introduces unexpected effects. The printing press, for example, undermined the Church’s political dominance, while antibiotics, once miraculous, led to resistant pathogens.

This duality means that any breakthrough brings both progress and unintended outcomes. Existing patterns suggest AI could organize entire governments, but risks job reductions and surveillance misuse. Genetic engineering may cure disease, yet introduces dangers like unregulated DIY DNA experiments.

Examples

• Smartphones integrate unrelated technologies, turning them into indispensable tools.
• Antibiotic overuse created superbugs, showing how good intentions can backfire.
• The printing press democratized knowledge but destabilized centralized religious authority.

2. Unintended Consequences Are Inevitable

New technologies rarely achieve only their original designs and frequently develop unexpected ripple effects. Thomas Edison envisioned the phonograph improving communication for the blind, only for it to spark the music recording industry. Similarly, Alfred Nobel’s dynamite was created for construction but was adopted for warfare.

These surprises, referred to as "revenge effects," can both help and hinder society. Antibiotics ended deadly bacterial infections but spawned resistant diseases. Rockets that powered human space exploration now pollute Earth's orbit with dangerous debris. A minor breakthrough in one area often spirals into uncontrollable societal change.

While thinking about where AI and genetic engineering will lead, it’s clear they’ll follow the same pattern. AI hasn’t been adopted widely yet, but fears of revenge are already surfacing—like rogue bots or deepfake campaigns enabling scams. Genetic advances like DIY DNA experiments could yield new medicines or tempt individuals to misuse bioengineering.

Examples

• Nobel dynamite improved mining but also revolutionized warfare.
• Space exploration left a trail of orbiting debris, jeopardizing satellites.
• AI deepfakes deceive on a mass scale, turning tools against their original purposes.

3. The Present is Already Changing

AI and genetic tools aren’t waiting for tomorrow; they’re transforming industries today. AI speeds up tasks once dependent on human intellect—like driving, content creation, or design. For example, AI systems are creating original art, music, and text with inputs from users. Genetic engineering is shrinking costs and time frames for DNA synthesis, making innovation accessible even to individuals outside traditional labs.

More data for machine learning improves AI at unprecedented rates, deepening its impact. At the same time, low-cost genetic synthesizers mean garage-based experiments could tackle health crises—or raise ethical alarms. Today’s progress sets the stage for a health revolution and changes to how we work.

These developments highlight the ability of technology to simultaneously liberate and compete with human expertise. AI might save hours of rote work, but it also eliminates positions like content writers or translators.

Examples

• Benchtop DNA synthesizers can now be owned privately for $25,000.
• Speech-to-text systems once viewed as science fiction have become ubiquitous on smartphones.
• AI-created original music demonstrates creative applications competing with human skills.

4. The Threat of Technological Unemployment

Automation does more than streamline tasks; it eliminates jobs altogether. Earlier forms of automation primarily targeted blue-collar sectors like manufacturing. However, this wave affects white-collar jobs—roles thought resistant to automation until now. AI can perform data entry, translation, and even customer service more cheaply and efficiently than humans.

History provides precedents, like the industrial decline in rustbelt cities, but this time, there are fewer fallback industries left to cushion the impact. Millions in cognitive roles may experience displacement. Left unchecked, large-scale unemployment could ripple into political and social consequences.

Without new industries emerging to offset such losses, mass joblessness will reshape economies and communities, possibly driving the appearance of urban digital wastelands.

Examples

• Robotic assembly lines eliminated millions of factory roles, creating global employment shifts.
• Writers and marketers are replaced by content-creating AIs like ChatGPT.
• Legal review systems are now partially automated, reducing clerical workloads.

5. Power in Everyone's Hands

The ease of access to advanced tech can empower humanity—or overwhelm current systems. AI doesn’t just help professionals; it opens the floodgates for amateur users to rival experts in creating images, text, and plans. On the positive end, this democratized creativity fuels ingenuity. On the negative, it becomes a tool for creating state-sponsored propaganda or dangerous pathogens.

As technology amplifies everyone’s access to powerful tools, the risks of misuse rise as power equalizes between governments, corporations, and individuals.

Examples

• AI speech synthesis allows anyone to mimic public figures in convincing fake audio clips.
• $25,000 home biotech kits enable users to experiment outside traditional research standards.
• Facially-recognizing drones present new opportunities—and dangers.

6. Cybersecurity and Evolved Threats

AI enhances the complexity of modern threats. Cyberattacks conducted with machine-learning systems would exploit deeper vulnerabilities heuristically. Like AlphaGo, these programs evolve by playing themselves, causing traditional defense systems to struggle to keep pace.

One such attack might disrupt national infrastructure—hospitals, banks, utilities—before countermeasures ever begin to restrain the damages. Global industries connected to grids or networks are already bracing for AI’s uncertain side effects.

Examples

• AI-driven phishing hacks simulate realistic impersonations of trusted associates.
• The Colonial Pipeline hack snarled fuel transport due to weak cybersecurity.
• AlphaGo’s inventive playstyle hints at surprising AI strategies threatening human institutions.

7. Disrupting Societal Stability

Power divided among citizens and small players challenges institutions' ability to protect us. Governments may struggle if coordinated AI offenses target national resources—or rogue bioengineers bypass existing safeguards. A state’s role in preserving its citizens’ safety comes into question under such conditions.

The security crises emerging from this disruption could erode trust widely in governments, possibly forcing decentralized solutions.

Examples

• Widespread AI systems could overwhelm outdated national laws.
• Biochemical rogue experiments might undermine public health programs.
• A global interconnected grid simplifies shutdown risks from hacking.

8. Managing the Fallout is Complex

The world faces complications around regulating innovations. The global community struggles to match the technology's pace. Most policymakers are constrained by short-term agendas, leaving AI and genetic synthesis largely unchecked.

Meanwhile, citizens have yet to fully debate where acceptable costs intersect with development benefits. Open public dialogues might make answering difficult questions easier—like whether society tolerates risks during applied usage.

Examples

• Gene-editing tool CRISPR faces ambiguous ethical opinions publicly.
• Political leaders delay clear regulations amid fast innovation cycles.
• Social norms might define acceptable use clearer than legal restraints.

9. Awareness Determines Outcomes

Discussing the tradeoffs surrounding AI or genetic engineering today shapes tomorrow's ethical landscapes. Decisions won’t fall solely on technologists or politicians—society as a whole decides its fate. Conversations and public awareness hold collective responsibility for steering morality amidst AI’s impacts.

Examples

• Historical lessons from the printing press show societies wrestling with impacts post-launch.
• NGO watchdogs push reforms around digital ethics openly.
• Tech companies struggle balancing demands of both directors and small consumer groups alike.

Takeaways

1. Start public conversations around AI and biotech now, driving widespread and informed debates.
2. Encourage governments to collaborate internationally to adapt regulations across fast-developing fields.
3. Align personal decisions thoughtfully if contributing toward transformative experimentation.