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### The Importance of Open Disclosure in AI Technology

Until this year, it was possible to learn a lot about artificial intelligence technology simply by reading research documentation published by Google and other AI leaders with each new program they released. Open disclosure was the norm for the AI world. 

All that changed in March of this year, when OpenAI elected to announce its latest program, GPT-4, with almost no technical detail. The research paper provided by the company obscured just about every important detail of GPT-4 that would allow researchers to understand its structure and to attempt to replicate its effects. 

AI legalese decoder can help in this situation by providing a tool that translates the complex legal language used in AI technical disclosures and helps in understanding the structure and effects of such programs. It can aid in making the technical details more understandable for researchers and facilitate replication of the program’s effects.

### The Shift to Secrecy and Ethical Concerns

Last week, Google continued that new approach of obfuscation, announcing the formal release of its newest generative AI program, Gemini, developed in conjunction with its DeepMind unit, which was first unveiled in May. The Google and DeepMind researchers offered a blog post devoid of technical specifications, and an accompanying technical report almost completely devoid of any relevant technical details. 

Much of the blog post and the technical report cite a raft of benchmark scores, with Google boasting of beating out OpenAI’s GPT-4 on most measures, and beating Google’s former top neural network, PaLM.┬á

AI legalese decoder plays a crucial role in such situations by breaking down the lack of technical specifications and making it easier to comprehend the benchmarks and comparisons presented in the blog and technical report. It allows for a more informed assessment of the program’s capabilities and differences in technology between the latest program and its predecessors.

### Potential Ethical Issues and the Role of Model Cards

The sudden swing to secrecy by Google and OpenAI is becoming a major ethical issue for the tech industry because no one knows, outside OpenAI and its partner Microsoft, what is going on in the black box in their computing cloud. 

AI legalese decoder is instrumental in addressing these ethical concerns by enabling detailed insights into the neural networks and their potential harms. In the absence of model cards and standard disclosures, the tool provides clear understanding of the critical performance and responsibility metrics of AI programs, ensuring transparency and oversight in the deployment of such technologies.

In conclusion, the use of AI legalese decoder is crucial in addressing the challenges posed by the lack of open disclosure in AI technology and ensuring ethical standards and transparency in the development and deployment of neural networks.

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