Estimating the Future of AI: A Practical Model of Overlapping Perspectives

 Estimating the Future of AI: A Practical Model of Overlapping Perspectives

By Zachary Chege

While the future can never be predicted with absolute certainty, we can make informed estimates by examining the perspectives of those most engaged with the development and implementation of artificial intelligence (AI). One effective method is to identify points of overlap among three distinct stakeholder groups:

• Promoters – Individuals or organizations that advocate for AI advancement, often driven by financial incentives or a visionary belief in its potential benefits.
• Resistors – Those who oppose or are skeptical of AI's rapid adoption, typically due to concerns over economic disruption or ethical implications.
• Implementers – The engineers, developers, and practitioners directly involved in building and deploying AI technologies.

Identifying the Overlap in Perspectives

Despite their differing motivations and outlooks, these groups often arrive at overlapping conclusions that offer the most realistic picture of what lies ahead.

For example, both Promoters and Resistors acknowledge that AI will inevitably replace certain jobs. Promoters frame this as a benefit—highlighting reduced operational costs and increased efficiency—while Resistors emphasize the negative consequences, such as rising unemployment and economic displacement. Despite their opposing values, they converge on the same fundamental prediction: AI will replace jobs.

Similarly, Implementers—those on the front lines of AI development—offer nuanced insights. Many developers note that current AI tools can produce bloated or insecure code. However, they also recognize that AI, when used strategically, can enhance productivity—automating repetitive tasks, identifying patterns in large datasets, and assisting in code quality assurance.

This balanced perspective suggests that while AI is unlikely to fully replace most complex roles in the near future, it is capable of automating simpler tasks and supporting more sophisticated workstreams. Therefore, the intersection of all three groups' viewpoints leads to a likely near-term outcome:

AI will continue to replace certain simple jobs and assist with aspects of more complex roles, rather than lead to complete automation across industries.

The AI Impact Estimation Model

This framework—based on identifying overlapping claims among Promoters, Resistors, and Implementers—can serve as a predictive model for assessing any proposed future impact of AI. The process involves:

1. Identifying the perspectives of the three stakeholder groups on a given AI-related claim.
2. Analyzing points of consensus among their positions.
3. Estimating the most probable outcome based on these shared insights.

By focusing on these intersections, we avoid extreme assumptions and instead derive grounded, evidence-informed predictions that reflect both technical realities and stakeholder dynamics.