Silicon vs. Biological

I recently posed an intriguing question to the latest (August 24, 2023) artificial intelligence system, GPT-4: > Is the biological stack of intelligence better than the silicone one?

Before we dive deep into the answer, allow me to provide a quick description of my intentions.

For all of human history, life has been confined to the biological stack - carbon-based organisms that evolved through natural selection. This includes humans and all other forms of life we know. This is nothing new. Yet in recent decades, a new stack has emerged - the silicon stack: digital “lifeforms” created from silicon. Silicon is a chemical element and the backbone of most computer chips and solar cells today. It has unique electrical properties that allow silicon-based technologies to enable the modern digital world. From powering devices, to enabling the internet, to assisting through AI - silicon helps drive innovation and connectivity across our society. Chips are now bricks.

Unlike biological life, silicon life is designed and engineered, rather than evolved. It can take myriad forms - from artificial intelligence like Siri, to algorithmic bots that populate social media, to virtual life simulated in game worlds. This new stack expands parallel to the old one, and has capabilities far beyond what our carbon-based bodies can do.

The rise of the silicon stack raises profound questions. How will these artificial lifeforms interact with biological society? Can we imbue them with human values? Should we grant them agency or rights? Will they surpass human intelligence over time, and what will this mean for our species? The boundaries between both stacks grow porous as technology becomes more integrated into human life. Understanding the differences and relationships between biological and silicon life will be a defining challenge in the 21st century. Though made of differing materials, both stacks shape the future of life on this planet.

Its nuanced response highlighted the complex tradeoffs between AI and human cognition. We humans have some distinct cognitive strengths evolved over millions of years. Our adaptability allows us to tackle novel environments and situations. Our general intelligence helps us extrapolate learning and apply skills flexibly. With integrated emotions, intuition, and sensory experiences, we can make holistic judgments. And our unparalleled creativity gives us the edge in realms like art, literature, and invention. However, humans also have limitations. Our thinking is relatively slow compared to machines. We are constrained by our finite lifespans and susceptibility to fatigue or disease. And the human brain, for all its capabilities, is prone to biases, fallacies, and inaccurate memories.

The benefits and drawbacks of artificial intelligence systems have complementary strengths that surpass human cognition. Their processing speed on data-intensive tasks is breathtakingly fast. They can scale massively once developed, unlike human expertise. Modern AI is extremely precise, objective, and focused when performing specialized tasks. It can find insights in seas of data that no human could. And it can operate tirelessly around the clock. But AI also faces shortcomings. Most systems lack generalized common sense and adaptability. They currently do not have sentience or consciousness. Their skills are confined to narrow domains. And they remain completely reliant on supporting technological infrastructure to even function.

Finding the Right Balance

Rather than an either-or competition, the ideal path forward involves a judicious combination of both types of intelligence. The proper balance depends on the problem at hand. While AI clearly excels at computational speed, humans remain superior at tasks requiring creativity and abstract thought. The future is likely to involve augmented intelligence - combining the best of silicon and carbon. A symbiotic relationship where AI enhances human capabilities and compensates for our limits. But this emerging reality also necessitates ongoing discussions around ethics and ensuring technologies are created and used for benefit, not harm. On the whole, artificial and biological intelligence each have distinct strengths and weaknesses. Selecting the “right” one is subjective and contextual. With prudence and foresight, we can harness the upsides of both to build a wise collaborative future.

Computer-generated art and music - algorithms can rapidly generate original artwork or musical compositions, but human creativity is still needed to curate, refine, and imbue the art with deeper meaning.

Video game design - games require computational power to render graphics, simulate physics, etc. But human creativity is crucial for storytelling, gameplay, and overall experience.

Engineering design - engineers use computer-aided design (CAD) software to iteratively test designs much faster than manual drafting. But human ingenuity is still needed for devising innovative new products.

Drug development - AI can swiftly screen millions of molecular combinations. But deciding which drugs to pursue further relies on human judgment and intuition.

Automated journalism - algorithms can generate news articles from data, but human writing skills add analysis and narrative flow.

Product recommendation engines - recommendation systems crunch data at scale to suggest products. But curating compelling collections still benefits from human merchandising.

Personalized education - adaptive learning software rapidly customizes lessons to students. But human teachers provide the creativity needed for engaging with diverse learners.

In essence, any domain that benefits from rapid computational analysis but still requires strategy, intuition, or creativity from humans can leverage the strengths of both artificial and biological intelligence. I feel that the future likely involves collaborative human-AI partnerships across many such fields. We will see.