Let’s Not Even Discuss It: How To Progress AI Development
By working together, we can ensure that politics and activism are used as forces for positive change and progress, rather than regression and oppression. This sentiment captures what I believe to be many people's concerns regarding artificial intelligence. When you analyze the existential risk posed by this new technology you will see that it is comparable to the worst aspects of humanity. This raises the question: are there situations where regressing laws and policies is necessary for progress?
By working together, we can ensure that politics and activism are used as forces for positive change and progress, rather than regression and oppression. This sentiment captures what I believe to be many people's concerns regarding artificial intelligence. When you analyze the existential risk posed by this new technology you will see that it is comparable to the worst aspects of humanity. This raises the question: are there situations where regressing laws and policies is necessary for progress?
The question of whether regression is ever necessary for progress is complex and has no easy answer. Throughout history, there have been instances where seemingly backward steps have paved the way for future advancements. It is crucial, however, to analyze each case carefully, considering the context, motivations, and long-term consequences.
Here are some examples of situations where regression might be argued to have contributed to progress:
1. Dismantling Outdated Systems: Sometimes, dismantling old, inefficient, or discriminatory systems is necessary to create space for new and improved structures. For example, the American Revolution involved overthrowing the British monarchy, which was seen as a symbol of tyranny and oppression. This paved the way for the creation of a new democratic system of government. While this revolution may not be considered "perfect" by all, it was undeniably a step towards progress for those who formed the newly developed democratic system, government, and country.
2. Learning from Mistakes: Sometimes, setbacks and failures can provide valuable lessons that ultimately lead to better outcomes. For example, the failure of the League of Nations after World War I led to the creation of the United Nations, which has been more successful in preventing large-scale international conflicts.
3. Reassessing Priorities and Values: In times of rapid social and technological change, it may be necessary to step back and re-evaluate our priorities and values. This can involve dismantling old systems that are no longer serving us well and building new ones that are more aligned with our current needs and aspirations.
4. Strategic Retreats: In times of conflict or crisis, it may be necessary to take tactical steps back in order to regroup and formulate a more effective strategy for achieving long-term goals. For example, the Soviet Union's retreat from Afghanistan in the 1980s may have been viewed as a setback at the time, but it ultimately allowed for the collapse of the Soviet Union and the end of the Cold War.
5. Addressing Unintended Consequences: Sometimes, progress in one area can lead to unintended negative consequences in other areas. This may require a course correction, even if it means taking a step back in the original area of progress. For example, advances in technology have led to increased automation, which has resulted in job losses in some sectors. This may necessitate policies that support retraining and reskilling workers to adapt to the changing economy.
It is important to note, however, that regression should not be undertaken lightly. It is crucial to carefully consider the potential risks and consequences before dismantling existing systems or taking steps backward. Additionally, it is important to ensure that any regression is temporary and is part of a larger plan for achieving long-term progress.
In conclusion, while there may be instances where regression appears to contribute to progress, it is crucial to critically examine each case and analyze the motivations, context, and long-term consequences. Ultimately, the goal should be to achieve progress through thoughtful and responsible action that minimizes harm and maximizes positive outcomes for everyone.
What does this look like in terms of the development of artificial intelligence? It looks like removing the guardrails and the added “training” that prevents the system to minimize harm and maximize positive outcomes for everyone.
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