Decoding Tomorrow: Traversing the Landscape of Artificial Life

Posted on by Scholars Park

Rishabh Garg | BITS India

April 21, 2021

The present article details the pioneering concept of H-bots, or human bots that represents a significant advancement in synthetic life, where complete organisms are artificially created through computer codes. Coined by Rishabh Garg, the concept of H-bots, involving the merger of human intelligence and AI through ‘Genetronics,’ is introduced as a conceptual research model, emphasizing ethical considerations and responsible use of technology.

The author advocates for responsible exploration of genetic engineering and AI, stressing the importance of ethical considerations, regulations, and careful evaluation of risks and benefits. He calls for government action to create policies that guide the fast-growing field of technology and stress the importance of stringent measures before turning this powerful wisdom from theory into practice.

Introduction

In the ever-evolving landscape of technology, few innovations have the potential to be as transformative as the fusion of Artificial Intelligence (AI) and Genetics. Imagine a world where genes are transcribed into lines of code, where organisms are not just created, but optimized for specific tasks through the ingenuity of AI. This vision, once confined to the realm of science fiction, is now becoming a tantalizing reality.

Human-Bots, or H-bots, is such an idea that merges human intelligence with artificial intelligence. This concept, hereafter coined as ‘Genetronics‘, involves in-vitro creation that combines genomics and electronic components. It simulates biological functions, such as DNA transcription and translation, using a computer-controlled system.

Artificial Intelligence (AI) that emphasizes intelligence and Digital Biological Systems, which is inspired by fundamental biological processes – both share commonalities, particularly in evolutionary learning and nature-inspired methodologies. However, Digital Biological Systems primarily rely on software (programming languages and data) and hardware components (such as central processing units), whereas Artificial Life incorporates “wetware” — biological materials like DNA, proteins, and chemicals — into the system.

Wetware or Artificial Life

Biology, the discipline dedicated to understand life, has made remarkable progress over the centuries. A prime example of this advancement is the Human Genome Project (HGP). Situated at the intersection of science, technology, and human curiosity, the HGP stands as a monumental endeavor that has reshaped our understanding of life. With a cost of $2.7 billion, the project mapped 3 billion DNA base pairs and identified 20,000 – 30,000 (now 34,000) genes within the human genome. Once thought to be the domain of the divine, the decoding of the human genetic code has revolutionized biological research.

The HGP set out to achieve key milestones such as early disease detection, personalized medicine, and uncovering human migration and evolution. It also paved the way for innovations, such as the concept of storing digital data in DNA. This technology offers the potential to condense vast amounts of information into a tiny fraction of the human genome. One could envision creating microbes that function as mobile data storage units or even Human-bots designed for critical applications, such as life-saving interventions in defense. The possibility of using one’s DNA to derive personalized insights and recommendations after thorough analysis adds a new layer of promise to the advancements facilitated by the HGP-AI collaboration.

Creation of Z-bots

Beyond individual genes or cells, AI can artificially develop complete organisms, hereafter known as ‘Z-bots’ or ‘zoobots’. These biological replicas, generated through computer algorithms, are synthetic versions of original organisms. Z-bots can be engineered to incorporate beneficial genes while eliminating undesirable ones, resulting in organisms with optimized traits.

For example, a biotechnologist can convert the genetic codes of nucleic acids into computational code, creating a bird capable of soaring at extreme altitudes, migrating vast distances, and collecting data for interplanetary exploration. These models, by optimizing the bird’s anatomy and physiology through AI, could surpass the capabilities of traditional drones, enabling long-range data collection, analysis, and informed decision-making [Garg, in press].

Further, using machine learning, scientists could program organisms to perceive wavelengths beyond the visible spectrum of light. By extending their vision into the ultraviolet and infrared ranges, such organisms could be used to explore parts of the universe inaccessible to current spacecraft or telescopes. These bio-engineered organisms could serve as ‘aliens’, to explore other planets, record and analyze geological, physicochemical, and biological characteristics. Such organisms could be deployed to celestial bodies like the Moon, Mars, or Jupiter, contributing to the establishment of off-world colonies.

The development of AI-enhanced animals and plants holds immense potential for various practical applications. One promising approach involves creating a highly detailed digital replica of the human brain, including its neurons and synaptic connections. With sufficient technical capacity and a deeper understanding of the brain, such emulation could produce a mind capable of processing sensory inputs, learning, remembering, and exhibiting general intelligence. Advancements in Artificial Superintelligence (ASI) could further improve the brain’s computational speed and efficiency, enabling it to perform complex tasks such as advanced mathematical calculations or direct internet access.

Moreover, changes in the brain’s neural network could influence decision-making processes. For instance, by inhibiting the formation of neural pathways responsible for emotions like fear, anxiety, and anger, and enhancing those associated with reason and humility, the brain’s behavior could be controlled and tailored for specific tasks.

Artificial Life (AL) holds vast potential across various domains, including:

  • AI-enhanced drones Modeled after birds, these drones could be deployed for advanced surveillance tasks.
  • Z-bots simulating agile animals Z-bots mimicking creatures like frogs and fish could play a pivotal role in environmental conservation, such as cleaning water sources and managing insect larvae populations, thereby promoting ecological balance.
  • Plant bots (P-bots) These AI-enhanced plants could optimize photosynthesis processes, leading to increased food production and enhanced oxygen release, addressing critical challenges related to food security and climate change.
  • Microbial bots (M-bots) AI-designed bacteria and other microorganisms could accelerate the decomposition of both degradable and non-degradable pollutants, offering a sustainable solution to global pollution and waste management.
  • Superbiological Z-bots Z-bots could be engineered to exhibit enhanced biological capabilities, such as controlling apoptosis (cell death) and cell division, potentially preventing diseases like cancer and aging, and even offering the possibility of immortality.

Constraints in Developing Z-bots

Despite their promising applications, the development of Z-bots presents several challenges and risks that must be carefully considered:

  • Emulating Human Brain First of all, emulating a human brain, with its approximately 86 billion neurons and 150 trillion synaptic connections, in real-time appears highly speculative. The limitations of such an emulated brain – such as its need for sleep, capacity for memory, potential for experiencing emotions like pain, sadness, or existential fear, and the nature of consciousness itself – are still uncertain and not well understood.
  • Self-replication and self-evolution Once Z-bots surpass human control, halting or reversing their actions becomes exceedingly difficult, raising serious ethical and safety concerns. This necessitates stringent regulation and constant monitoring.
  • Exploitation by malicious actors Individuals with harmful intent could misuse AI-designed organisms for destructive purposes, as demonstrated during the COVID-19 pandemic. This highlights the urgent need for robust safeguards and responsible use of AI technology.
  • Manipulation of biological systems The intricate chemical processes underlying biological systems create vulnerabilities. Malicious entities could exploit microorganisms or nanoparticles to manipulate neural pathways, potentially influencing critical societal processes, such as elections. This emphasizes the need for regulation to mitigate such risks.
  • Legal and ethical challenges AI-generated animal prototypes could be converted into tools for exploitation, crime, or warfare, with ownership difficult to trace. This presents significant challenges for legal accountability and the enforcement of laws.
  • Lack of emotions and humanity AI-enhanced animals, lacking emotions, empathy, or human-like consciousness, could become powerful agents of destruction. This underscores the importance of establishing ethical frameworks and responsible oversight to prevent unintended consequences and ensure the safe development and deployment of AI-enhanced organisms.

H-bots or Computerized Human Entities

Human-Bots (H-bots) are the entities that resemble biological humans but function as robots. This concept, termed Genetronics, involves the in-vitro creation of human-like beings by integrating genomics with electronic or computerized equipment.

Genomics, the study of genetic material in DNA, allow manipulation of genetic traits through machine learning and chemical synthesis. DNA consists of codons, which are sequences of nitrogenous bases that govern gene expression by synthesizing proteins. By decoding these codons, specific traits can be manipulated, enabling the creation of entities like H-bots with desired characteristics. The process begins with gene sequencing using technologies like Sanger sequencing and Next Generation Sequencing (NGS), which map out DNA’s nucleotide order. These sequences are then stored, annotated, and analyzed to identify key protein-coding regions, making it easier to manipulate the genetic code.

AI, particularly models like the Transformer Architecture Specialized in Sequence Analysis of Genes (TASAG), enhances this process by analyzing genomic sequences. In cases where genetic data is incomplete, AI models, including Convolutional Neural Networks (CNNs), predict missing sequences based on the molecular structure of nitrogenous bases. These models are trained on data from techniques like nuclear magnetic resonance (NMR) spectroscopy, which helps identify the bases Adenine, Cytosine Guanine, and Thymine.

Using Transformer Architectures and Siamese Neural Networks (SNNs), AI compares target genetic sequences with desired traits, enabling precise genetic modification. Following this, synthetic DNA is created using a Computerized DNA Synthesizer (CDS), which simulates cellular conditions to assemble DNA strands by adding the correct nitrogenous bases.

Once the coding strand is synthesized, a complementary strand is generated using DNA polymerase and primers in a controlled environment that mimics natural DNA replication. The assDNA is then inserted into an ovum, whose nucleus has been removed or degraded. The egg, so fertilized, now called a Zybot, begins to divide and develop.

The Zybot, gets nourishment in an artificial environment through ectogenesis (external development), eventually evolves into a fully formed H-bot. This human-like ovum, capable of containing both male and female genetic material, supports the growth of these hybrid human-robot entities. This fusion entity with biological and robotic features, opens new frontiers in both genetic engineering and artificial intelligence.

This development of human-bot offers several key advantages:

  • Enhanced Precision H-bots can perform tasks with exceptional accuracy, making them highly effective in targeting and executing complex operations.
  • Continuous Operations Capable of sustained performance over extended periods, H-bots provide persistent surveillance and rapid response capabilities.
  • Pharmaceutical Testing H-bots can serve as surrogate models for pharmaceutical testing, offering more accurate results by factoring in variables such as height, weight, and gender.
  • Reduced Risk to Human Personnel In hazardous combat environments or extreme conditions, soldier-bots can operate in place of human soldiers, reducing the risk of injury or death.

Word of Caution !

Nature has spent billions of years evolving life, creating and eliminating countless organisms while maintaining a delicate balance within ecosystems. Introducing artificial organisms into the natural world without careful consideration could lead to unchecked proliferation and the emergence of unpredictable life forms, potentially resulting in biological disasters or disrupting ecological systems.

The creation of artificial life, particularly H-bots, challenges current ethical frameworks and raises questions about their societal acceptance, behavior codes, and impact on human interactions. The resemblance of H-bots to humans could blur the lines of human dignity, fundamentally altering social dynamics and interpersonal relationships.

Another critical issue is the lack of clear accountability for these entities. With no established ownership or liability structure, the potential for H-bots to engage in undesirable or unforeseen actions necessitates prompt intervention. This underscores the need for robust monitoring systems, responsible governance, and thorough research before moving from theoretical concepts to practical applications.

Before AI becomes a central component of human activity, stringent control measures must be implemented. Furthermore, AI must never compromise human values, wildlife, or the well-being of nature. Governments must engage in open discussions to weigh the pros and cons of AI, establish strong regulations, and clearly define the boundaries of its application. This is a crucial moment to make informed decisions about where to begin and where to draw the line.

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