Technology moves in cycles and AI is all over the news and media, making it a darling of this current lifecycle. As a an optimistic skeptic I want new tech to succeed, but I do not immediately understand why. This post is part of a larger series where I explore this space to understand the tech and identify potentials for value.
To explore and understand, I will be illustrating my ideas and hypothesis’ of where I think AI and tech is heading. Theorizing is fun, but I enjoy getting involved so where possible, I plan to conduct experiments to test the hypothesis and prove them out.
I am not building alone nor at the speed of light, some if not all of my hypothesis’ are being attacked by major players. I will call out those projects/products/companies and explore their solutions. It will be interesting to see how my thoughts align and are being addressed.
Below are my hypothesis of where AI is going.
Hypotheses
- AI will be a layer between humans and data.
- ex. AI systems share data vs Google Search/Wikipedia/Blog post
- Large scale automation will grow.
- ex. user input blog post title. AI writes post, adds images, posts to blog, shares links on social media, responds to interactions.
- ex. base_user asks system to find specific users by X type in their personal network. Open communication with them (email, sms) and progress conversation before passing successful person over to the base_user
- Inbound Customer Service will decrease in human footprint by at least 25%
- ex. the phone tree and chat systems have AI integrations. All interactions have to progress through AI until a human is required. AI is trained on all documentation, links, has access to simplistic control systems (check calling user status, resend test signal, refund small amount of money, etc).
- Outbound SDR outreach will decrease in human footprint by at least 25%
- ex. base_user asks system to find specific users by X type in their personal network. Open communication with them (email, sms) and progress conversation before passing successful person over to the base_user
Additional Hypotheses
1. AI-Powered Personal and Professional Development
Hypothesis: AI will become a personalized mentor and coach.
Challenges: Ensuring accurate and unbiased recommendations and maintaining privacy and data security.
2. AI in Creativity and Design
Hypothesis: AI will co-create with humans in fields like art, music, and design.
Challenges: Managing the intersection of technology and creativity while ensuring originality and authenticity.
3. AI in Healthcare Diagnostics and Management
Hypothesis: AI will augment healthcare by improving diagnostics and patient management.
Challenges: Ensuring accuracy, reliability, and ethical management of healthcare data.
4. AI in Sustainable Practices and Environmental Management
Hypothesis: AI will facilitate more sustainable operations and resource management in various sectors.
Challenges: Adapting AI algorithms to diverse and dynamic environmental conditions and ensuring accessibility across various sectors.
5. AI in Enhancing Emotional Intelligence and Human Interaction
Hypothesis: AI will enable machines to understand and respond to human emotions more effectively.
Challenges: Developing technology that accurately interprets a range of human emotions and responds appropriately without being perceived as intrusive.
6. Decentralized AI Systems
Hypothesis: Decentralized AI systems will emerge to enhance privacy and data ownership.
Challenges: Ensuring robust, secure, and efficient decentralized AI systems.
7. AI in Global and Local Governance
Hypothesis: AI will play a crucial role in decision-making processes in governance at various levels.
Challenges: Managing ethical considerations, bias, and ensuring the inclusivity and fairness of AI-driven governance.
Next Steps
We will conduct experiments to test the above hypothesis. Any suggestions on which experiment to run first? Has anyone solved these points? Exciting times ahead, looking forward to documenting all my explorations into AI.
Cheers
Nigel A.