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Thinking of the Future Based on Today

To evaluate AI innovation and arrive at ethical determinations, one must have a forward-seeking perspective and be averse to hype cycles, moral panics, and profit-only motivations.
Hype cycles >
Moral Panics >
Profit-only motivations > 
Optimism or Doom >
Glass Flower

Optimism about the future is only warranted when we can objectively look at the past and choose differently for the future. Meeting this moment will require great thought, new ideas, and a shift in perspective and accountability.

NEXTGEN ETHICS' Thought Leadership: While these theories and published ideas are pending copyright, they are unavailable for download. But we're always up for a chat about these views! >

Perception of AI
Broken Mirror Theory

AI Frameworks

Deployer and User Framework

Knowledge Framework

Tripartite Holistic Framework

Child Protection

Online Child Protections Research and Findings

Anthropomorphism of AI

The Spectrum View



Harms of Training AI on the Trainers of the Global South

OpenAI used Kenyan workers to label and identify harmful content. The work was so traumatic that the contract was canceled 8 months early. The pay - $2 per hour. Future contracts are also refused.

Learn more about this >

Data Scraping and Ownership of Information

Many lawsuits mentioned above involve the scraping of data from public information online. This is despite copyright protections listed on the information. While this might sound like a "them" problem. You are one of them and your information was included also.

The Business Impact of Web Scraping >

Drain of Environmental Resources:

Water usage is a significant impact of artificial intelligence because it is used to cool data centers. However, that's not the only environmental impact. Others concerns are emissions, waste disposal, energy consumption, and land use.

AI is Accelerating the Loss of Our Scarcest Natural Resource: Water >


From being inaccessible based on assistive needs and language/voice barriers, to the persistent lack of gender diversity in the tech industry, to the unfair consequences faced by marginalized communities, societal challenges like these are all too familiar in the realm of AI.

Artificial Intelligence and DEIA Efforts >

Bias and Privacy Across the AI Lifecycle


From training the AI system, to its deployment and use case, to the impact on the customer or society it is released into. AI has a bias and privacy problem that risk mitigation alone cannot fix.

Ethical and Social Implications of AI Use >

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