Technology

Propulsive

Technology is an accelerant. At increased speeds, conflict happens and any direction becomes arduous to command.

Welcoming the confluence of humans and machines reduces the gap between human potential and artificial intelligence. Positive intent with ethics at the forefront of progress may help avoid an imbalance, but there’s still no guarantee that comes with our trust in technology.

This means we must remain inquisitive. Pushing elephants into the room encourages critical thinking, invites problem-solving, and provokes new perspectives. Complacency leaves room for degraded integrity, so here are a few brain teasers to help us rise above cliché conversations.

  • What is worth sacrificing to achieve progress?
  • A single AI prompt uses roughly the same energy as running a light bulb for 15 minutes. Adaptive computing, alternative energy, and other bridges to tomorrow will support more efficient interactions, but how might careless consumption impact long-term sustainability?
  • Might unlimited access lead everything to be mediocre?
  • With an answer always available, how can we celebrate experiential wisdom to maintain a willingness to learn?
  • Will enhanced productivity make humans lazy?
  • How is time spent when tasks are no longer a concern?
    • How do humans avoid isolation when technology makes perceived connection effortless?
    • If the Internet is dominated by AI-generated content, might the overwhelming slop tempt exhausted humans to hibernate? As disconnected vaults form, will the beauty of collaboration and our connected era be lost?
    • Could the story of money ever get old?
    • Do we really care about privacy or is it that we just never like feeling surprised or exploited?

      The ethical aspects of technology can feel like a drag. Unfortunately, the ease of overlooking short-term issues usually leads to long-term problems.

      To find an equilibrium with artificial counterparts, elevate what we’re good at and do the same with technology, but slow down to avoid irreversible damage. As we align answers together, trust in a shared direction celebrates limitless diversity, while ensuring a future that respects the past and remains open to next.

      By Ben McDougal, ago

      Septenary

      AI is often thought of as a singular technology. This blanket assumption makes it impossible to compare the capabilities and functionalities that differ between the seven different types of artificial intelligence.

      The seven types of AI are organized into two groups. The first group is based on capability and includes Narrow AI, General AI, and Super AI. The second group is based on functionality and includes Reactive Machine AI, Limited Memory AI, Theory of Mind AI, and Self-Aware AI.

      Capabilities are determined by what different types of AI are able to accomplish. The three types of AI categorized by capabilities are Narrow AI, General AI, and Super AI. Here’s a rundown to leverage what’s possible today, while staying mindful of what may be possible tomorrow. 

      Narrow AI <realized>

      AI trained from existing data, with compute geared to do one thing really well. While data sets are vast, this type of AI can not go beyond the data sets it is tied to. As of 2026, Narrow AI is the only type of AI that is fully realized within the three types of AI categorized by capabilities. Examples of Narrow AI include language translators, game-playing programs, spam filters, recommendation engines, voice assistants, facial recognition, self-driving vehicles, and robots with specific tasks. Generative AI also falls within this type of AI, which seems odd. The mashups of generated text, images, video, and sound seem to be random, but are still constraints by existing data sets. Neural networks, optimized data sets, computer vision, and machine learning make the capabilities of Narrow AI remarkable, but limited by the data it has to munch. 

      General AI <theorized>

      This advancing realm of AI leverage existing data like Narrow AI, but can reason beyond those constraints. The transfer of intelligence, with no human intervention, makes the race to General AI (also called AGI) intense. When AI can make decisions based on an advancing state of its own understanding, the limit of this AI’s capabilities become unknown. Theories set the potential limit around that of a human. Agentic AI hints at AGI with decision making and interdisciplinary task management, but lacks the emotional traits, planning, and other methods of generalization that will define the capabilities of General AI. Other potential examples include all-new content creation, robots that can learn new tricks. As the theories of AGI become realized, ethics, regulation, and a determination of consciousness will be moving targets to navigate. The breeding speed of AGI may release points of no return, which makes it critical to understand and debate opening to ensure a new species is copacetic. 

      Super AI <theorized>

      Welcome to when AI becomes it’s own species. Concern triggers due to the finite resources of Earth, but when AI surpasses the capabilities of humankind, dust from the deep future will already be everywhere. Multi-planetary travel will be underway, climate problems will be solved, and life extension will be supported by Super AI. Singularity is theorized to push the functionalities of Self-Aware AI and the capabilities of Super AI beyond humanity’s control. This means the time to plan ahead is now. As the minds of machines are wired, it’s crucial to collectively consider the heart and soul we build into technology. This will guide discovery with an excellence that came before it.

      AI based on functionality is less about power and more about how things works. Reactive Machine AI, Limited Memory AI, Theory of Mind AI, and Self-Aware AI are the types of AI classified by their functionalities.

      Reactive Machine AI <realized>

      This is old school AI. Rooted in statistical math, Reactive Machine AI arrived soon after the programmable computer was developed. There is no adaptive learning here, but the speed at which it can calculate a vast amount of data makes the performance seem intelligent. The functionalities of Reactive Machine AI drives more primitive examples of Narrow AI, such as recommendation engines and game-playing programs. This type of AI provides a static base, but with no memory and only a focus on specific tasks, attention quickly shifts toward functionalities that have more adaptive characteristics.

      Limited Memory AI <realized>

      This type of AI learns and evolves. Functionalities of Limited Memory AI are still constrained by the existing data it was trained with, but world-changing advancements have been seen in machine learning, large language models (LLMs), generative AI tools, multimodality, computer vision, and self-driving vehicles. The realization of Limited Memory AI has Narrow AI pushing it’s full potential.

      Theory of Mind AI <theorized>

      Here we combine existing data, an adaptive ability to learn, and an emotional willingness to think. Enhanced reasoning, multimodality, customizability, adaptive computing, and user-driven functionalities bring General AI (AGI) to life. Theory of Mind AI embraces emotions and understands how we think. This type of AI will add personality to humanoid robots and support reliable relationships by combining digital depth to the realities of our world. As lines blur between humans and machines, compute will remain a currency, efficiency will skyrocket, and a new era of life on earth will begin.

      Self-Aware AI <theorized>

      It’s hard to define consciousness, but true self-awareness exemplifies this type of AI. Along with understanding how we think, Super AI will own emotions, hold beliefs, and is theorized to support the functionalities of Super AI.

      Understanding the seven types of AI helps leaders leverage the perks of technology now and later. Our willingness to lift the fog helps avoid a fear in the unknown and while resisting technology is a choice, it’s one that may put you behind innovation curves. Hybrids add artificial co-pilots, but remain assertive and budget resources knowing we are the pulchritudinous architects of our own neon future.

      By Ben McDougal, ago

      Innovation Curves

      Things happen. Trends occur. Economies shift. Technology jolts the systems. Culture changes. Time will do its thing.

      Amidst change, it’s easy to hold on to what worked before. Innovation curves are hamster wheels that are hard to stay ahead of. The term itself creates circular conversation. “Innovation” is abstract and often over-used. Everyone experiences innovation, but just because we try something new, doesn’t mean we’re a thought leader on change. Gurus will guide and teams can make it easier to stay ahead of your own innovation curves, but it’s never easy.

      When stagnant, work feels like work. Maintain what built existing momentum. Continue delivering on the promise, then experiment to remain in-tune. Stay thirsty enough to tinker. Add diversities. Make new early moves. Understand risks. Remain connected to end-users to grasp reality. Own what’s needed and hold on tight.

      Time will still pass and every story will end. The best ones are those we chose to end on our own terms.

      By Ben McDougal, ago

      Cyberspace

      The Internet linked our planet. It ignited an information age and now supports our connected era where humanity’s collective intelligence dials into boundless potential.

      The vast, yet connected nature of cyberspace is what makes knowledge accessible to anyone. It makes communication instant, gives founders an ability to scale, and helps anyone find their tribe. As artificial intelligence (“AI”) taps into the treasure trove we’ve been building since the 1960s, we’ve seen how quickly technology can advance thanks to the endless contributions of generational leaders worldwide.

      Heightened connectivity will take us into the deep future, but be wary of excessive consumption. With everything at our finger tips, it’s easy to get lazy. This can degrade our mental fitness with isolated ideology confidently misguided by algorithms. We may be the last generation to know what life was like offline. This enshrines a calling to embrace emerging technologies, but also to preserve the communal code that nature, experiential wisdom, relationships, and eccentricity uploads into the human experience.

      By Ben McDougal, ago

      Digitized Consciousness

      Would you choose to live forever? Most people say no. There’s something precious about the finite nature of life.

      That said, making an impact, life extension, endowing loved ones, and leaving a legacy are common ambitions.

      As humans merge with machines, digitizing our life’s body of work can technically already be done. To illustrate this, the average human generates around two gigabytes per day. This data culminates from the text, audio, photos, video, and other creative expressions we create. Nanotechnologies may reduce the storage space needed, but even without that multiplex, if we generate 730 gigabytes of data each year and live 75 years, that equates to only 54,750 gigabytes, which is less than 55 terabytes. Everyone generates different types and levels of information, but storage is not the issue.

      With storage negligible, creation of content, organization, and privacy concerns will always present barriers. Barriers are built to be broken, yet information alone is unlikely to represent the enigma of one’s consciousness. The totality of one life’s output will present signals, but if those who follow are to interact with a digitized consciousness, how might the experience need to be supplemented to feel organic?

      Interfacing with the brain will unveil depth in the human mind, but will that be enough to paint how consciousness is felt though the heart and soul of our existence?

      Replicants with your digitized consciousness may never fully represent the original, but this won’t stop such a resource from being appreciated. Whether it’s stories told, wisdom shared, or just a voice to comfort our descendants, humans thrive thanks to a historic desire to pass our experience to future generations. As we continue to digitize the world, the option for mind uploading seems inevitable and organized content creators may have a head start.

      Extra Shot

      Consumption expires.

      Create to live beyond time.

      Let’s assume advancements in brain-computer interfaces, neural networks, and quantum computing unlocks the ability to effectively digitize consciousness. Who might activate it and how would such an asset be portrayed, owned, and managed after the human passes away?

      Navigating this reality will require a combination of legal, ethical, and philosophical frameworks, but eventually, the digital interaction becomes easy. It gets weird as this digital asset becomes a part of the physical world. What might a digitized consciousness paint on a canvas? Why not mix sounds into music? Could it run a humanoid robot?

      Further down the road, what are potential risks and benefits of creating a digitized consciousness that is capable of self-improvement and adaptation? Final alignment may be needed before the human dies so tiny details could be refined. Even with final tweaks to support transcendence, software gets stale, but updates could alter the asset.

      It feels important to evolve elements that keep such an asset functioning, but the ideas, insight, perspectives, and overall interaction with such a digitized consciousness would need to be unscathed to remain true to the original source. If an uploaded mind was altered, a kind of digital entropy would fragment the asset away from its original purpose.

      A transforming heart may keep this asset in vogue, but the identity of the human it represented would be lost. Any digitized consciousness will become outdated over time, but perhaps that will be part of the charm.

      By Ben McDougal, ago