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DataEthics4All's Ethics 1st Data and AI Alliance

Ethics 1ˢᵗ Data and AI Alliance

to

Build an Ethics 1st Data and AI World!

The Mission.

DataEthics4All Foundation’s Ethics 1st Data and AI Alliance recognizes that AI technologies including Generative AI have the potential to impact society in significant ways, and that it is important to ensure that these technologies are developed and deployed in a responsible and ethical manner.

The Alliance is for Companies who agree with the challenge and would like to come together to build Responsible Data and AI Practices and Solutions.

The alliance brings together industry leaders, academics, and experts from various fields to develop a set of principles and best practices for responsible AI development and deployment.

By providing a platform for collaboration and exchange of ideas, the alliance seeks to create a community that is committed to advancing ethical practices in the development and deployment of AI technologies.

Learn how your Company can become a ‘Founding Member’ of the Ethics 1st Data and AI Alliance.

Ethics 1st AI MMI.

Ethics 1st AI Maturity Model Index by DataEthics4All Foundation. A Benchmark to help a Company measure and improve their Ethical Data+AI Practices internally.

Introducing The Ethics 1st AI MMIᵀᴹ !!

A first ever Benchmark to help a Company measure and improve their Ethical Data+AI Practices internally.

An Ethics 1st AI Maturity Model Indexᵀᴹ is needed for several reasons:

Ethics 1st Data and AI Alliance.

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Ethics 1st AI Alliance Interest Form
Step 1 of 3

Framework 2.0.

1. Building responsible tech with ethics woven into the fabric by design.

2. Promoting end-to-end data governance across organizations to guarantee ethical data use.

3. Ensuring cognitive diversity (demographic and functional diversity) and inclusion in human oversight for building and auditing the next generation of AI models and systems.

The 12 Ethical Pillars.

DataEthics4All-12-Ethical-Pillars

Presenting The 12 Ethical Pillars Of The DataEthics4All Framework 2.0

1. Preserving Data Privacy

Preventing the violation of data privacy and data mishandling through non-consensual sale to third parties.

2. Fair Data Processing

Ensuring that data gathering and processing from multiple sources is done fairly and without manipulation through aggregation.

Ensuring that power in data processing is applied with a clear understanding of the influence on the results and consequences on the data subjects.

Ensuring that individual data subjects are able to retain their anonymity.

3. Preventing Data Misuse

Ensuring there is no inappropriate use of data as perceived by the data subject when data was initially collected.

4. Clear Data Ownership

Advocating for clear understanding of ownership and accountability of personally identifiable information. (PII)

5. Explicit Data Consent

Ensuring there is explicit data consent for the personal information obtained directly from a customer, and that all parties are fully aware of the use and benefits of that data.

6. Data Power and Control

Preventing companies from taking unlimited control over personal data.

Preventing the non-transparent and uncontrolled proliferation of data transactions.

7. Data Transparency and Trust

Giving customers control of their personal data and earning their trust and goodwill.

8. Data Quality Auditing

Preventing unfair discrimination by auditing the quality of data and ensuring that the available data is representative of the whole population or phenomenon of study.

9. Interdisciplinary Algorithmic Auditing

Detecting confirmation biases and other biases in Artificial Intelligence Models through Interdisciplinary Algorithmic Auditing.

10. Combating Deliberate Disinformation

Combating deliberate disinformation via fake news and misleading memes by making sure our technology verifies news sources before amplifying them.

11. Preventing Ad Technology Weaponization

Ensuring that our social media platforms and ad technologies are not being used for political and personal gain.

12. Evolution of Data Ethics in Times of Crisis

Understanding the evolution of data ethics, privacy, consent, transparency, etc., in times of crisis.

Detecting crisis-driven scams and other attacks on data-based processes.

Preventing the introduction of nefarious malware which could impact the outcome of data analysis.

The Canvas.

What are our methods to achieve this?

1. Ethics 1st Data and AI Alliance

The development and deployment of artificial intelligence (AI) technologies have the potential to bring about significant benefits to society.

However, AI systems also raise important ethical concerns, including issues related to bias, privacy, transparency, and accountability.

It is crucial that we ensure that the development and deployment of Data and AI Platforms and Solutions is guided by ethical principles that prioritize the well-being and interests of all individuals and communities.

The Ethics 1st Data and AI Alliance is one of the initiatives that aims to promote ethical development and deployment of AI technologies.

2. Engaging Industry Experts

We engage credible industry experts from various fields to understand and keep up with data science and AI ethics best practices and trends.

3. Providing Thought Leadership

We work with informed opinion leaders and trusted sources who have the ability to move, inspire and influence.

4. Fostering Community Discussions

The DataEthics4All Community platform levels the playing field for individuals to come together and openly share their views and concerns on the subject of data science and AI ethics and the many challenges of data compliance, governance, generative AI and data privacy for businesses and consumers.

5. Conducting Market Research

We employ scientifically-led studies to enable stakeholders to be aware of trends and challenges in data and AI ethics, and to generate solutions.

6. Enabling Learning Opportunities

DataEthics4All enables blended and connected learning which combines personal interests, supportive relationships, and opportunities.

Ethics 1st development in Data and AI.

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