The Mission of DataEthics4Allᵀᴹ Foundation, a United States Presidential Volunteer Service Award (PVSA) Certifying Organization is to Build an Ethics 1stᵀᴹ Data + AI World with Ethics 1st Data + AI Champions!
We provide Professional Development, Leadership, Volunteering, Learning, Upskilling, Reskilling, Networking, Jobs, Returnship and Internship Opportunities in Data + AI Ethics to Middle School, High School, College Students, Educators, Academic Leaders, Researchers and Professionals.
Our STEAM in AI Initiative aims to democratize artificial intelligence education and empower the next generation of tech leaders with a strong ethical foundation.
We aim to break down barriers of entry into the tech industry for economically disadvantaged students, girls, women, and people of color through comprehensive education and mentorship.
Our programs focus on providing accessible, high-quality education in Science, Technology, Engineering, Arts, and Mathematics (STEAM), with a strong emphasis on AI, to prepare students for the future workforce.
By fostering an inclusive and diverse learning environment, we strive to build an equitable future in technology.
Our Premium Community has members: Data + AI Ethics Leaders, Practitioners and Students from 71 Countries across the Globe.
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The Framework V2: 12 Pillars.
Presenting The 12 Pillars of DataEthics4All Foundation’s Ethics 1stᵀᴹ Data and AI Framework (Revised in 2023)
1. Responsible Data Collection and Use
This pillar focuses on starting at the drawing board with a clear purpose and a use case. What is it that we’re trying to do and what data do we need for that?
Avoiding the collection of unnecessary or irrelevant data is a key aspect of responsible data collection and use. Collecting data without a clear purpose or understanding of how it will be used can lead to data hoarding and potential privacy and security risks. It can also contribute to the perpetuation of biases and inequalities, as data that is not relevant or necessary for a given task may still contain sensitive or personal information.
Instead, organizations should adopt a “data minimization” approach, which involves collecting only the data that is necessary and relevant for a specific purpose. This includes understanding the context of the data and considering the potential benefits and risks associated with collecting and using it.
Adopting this approach requires a shift in mindset, away from the notion that “more data is always better” and towards a more deliberate and responsible approach to data collection and use.
2. Data Transparency and Trust
This pillar emphasizes the importance of transparency in communicating to the data subjects what data is being collected, how it will be used, and who will have access to it.
This includes providing clear and accessible privacy policies and terms of service.
3. Explicit Consent
This pillar requires obtaining explicit, informed consent from the data subjects before collecting and using their data.
It also includes providing the option to opt-out of data collection and use.
4. Sunset Policy
This pillar involves having a clear and specific timeframe for how long data will be retained, after which it will be deleted or anonymized.
5. Data Privacy and Security
This pillar highlights the importance of protecting data subjects’ privacy and ensuring data security.
This includes avoiding collecting personally identifiable information (PII) and implementing robust security measures to protect against unauthorized access, breaches, and data misuse.
6. Data Brokering
This Pillar prohibits Companies from unlimited control over personal data and on the non-transparent and uncontrolled proliferation of data transactions including selling or exchanging of personal data for commercial purposes without explicit consent from the data subjects.
7. Data Inclusivity
This pillar focuses on ensuring that data and AI systems do not perpetuate or exacerbate existing biases and inequalities.
This includes ensuring that data and AI systems are designed to be inclusive of all individuals and groups, regardless of demographic factors.
8. Data Power and Control
This pillar addresses the power dynamics inherent in data and AI systems and emphasizes the importance of giving data subjects control over their own data.
This includes providing mechanisms for data subjects to access, edit, or delete their data as well as giving them agency in decision-making around data collection and use.
9. Disinformation and Polarization
This pillar involves taking steps to mitigate the spread of disinformation and polarization through data and AI systems including content generated by Generative AI Tools and systems.
This includes promoting fact-checking and accuracy in data and AI systems and minimizing the amplification of harmful or divisive content.
10. Algorithmic Auditing
This pillar involves regularly auditing and testing AI algorithms to ensure that they are fair, transparent, and unbiased.
This includes testing for bias and unintended consequences and being transparent about the algorithmic decision-making processes.
11. Interdisciplinary Auditing
This pillar emphasizes the importance of interdisciplinary collaboration and ethical oversight in data and AI systems.
This includes involving stakeholders from different disciplines and fields from within the Company, including technical, social, and legal experts, in auditing and governance processes.
12. Independent Body Review
This pillar involves having an independent body or regulatory agency responsible for reviewing and overseeing data and AI systems to ensure compliance with ethical principles and legal requirements.
This includes ensuring accountability and transparency in decision-making and mitigating potential harms to individuals and society as a whole.
What is Ethics 1st?.
What does Ethics 1stᵀᴹ in Data and AI mean?
Ethics 1stᵀᴹ in Data and AI refers to an approach to data and AI management that places ethics at the forefront of decision-making.
It involves prioritizing ethical considerations such as privacy, security, fairness, and transparency in all aspects of data and AI use.
Ethics 1st in Data and AI is based on the belief that ethical considerations should be integrated into the design, development, and deployment of data and AI systems, rather than being an afterthought or add-on.
The Ethics 1st approach recognizes that data and AI have the potential to impact individuals and society in profound ways, and that ethical considerations must be taken into account to avoid harm and ensure that these technologies are used for the benefit of all.
Ethics 1st in Data and AI requires a commitment to ongoing education, reflection, and dialogue on ethical considerations and their implications for data and AI use.
Overall, Ethics 1st in Data and AI represents a shift away from a purely technical or business-focused approach to data and AI management, and towards a more holistic approach that recognizes the importance of ethics in building trustworthy and sustainable data and AI systems.
Ethics 1stᵀᴹ = Ethics by Design. Ethics in the DNA. People above Profits mindset.
For Data 1st and AI 1st Companies!!
Ethics 1st AI Score.
The Ethics 1st AI Scoreᵀᴹ by DataEthics4All Foundation is the first ever Score designed to help Companies measure their commitment to ethical Data+AI practices from the lens of their Employees and Customers.
The score is meant to provide a standardized way for employees, customers, and other stakeholders to assess a company’s ethical practices related to Data+AI.
By earning a high score, companies can demonstrate their commitment to ethical practices and build trust with their customers and stakeholders.
Ethics 1st AI Scoreᵀᴹ = A Score of Compliance + Trust by Employees and Customers
A Company’s Ethics 1st AI Scoreᵀᴹ can help create a more transparent, accountable, and ethical Data and AI world, which can benefit both Companies and Consumers.
As Seen In.
Ethics 1st AI MMI.
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:
Provides a framework for measuring progress:
An Ethics 1st AI maturity model index provides a framework for assessing a company’s progress in adopting ethical data and AI practices.
By providing a clear structure for measuring progress, it enables companies to identify areas where they need to improve and track their progress over time.
Encourages adoption of best practices:
A maturity model index provides guidance on the best practices for ethical data and AI use.
By following the model, companies can ensure that they are implementing the most effective strategies to address ethical concerns related to data and AI.
Helps companies prioritize investments:
An Ethics 1st AI Maturity Model Index can help companies prioritize investments in ethical data and AI practices.
By identifying the areas where they need to improve, companies can make informed decisions about where to allocate resources to have the greatest impact.
Enables benchmarking:
A maturity model index allows companies to benchmark their progress against other companies in their industry.
This can help identify areas where a company is lagging behind its peers and provide insights into best practices that can be adopted.
Fosters a culture of continuous improvement:
An Ethics 1st data and AI maturity model index fosters a culture of continuous improvement by encouraging companies to regularly assess and improve their ethical data and AI practices.
This can help create a culture where ethical considerations are at the forefront of decision-making processes.
Overall, an Ethics 1st data and AI maturity model index provides a valuable tool for companies to measure progress, identify areas for improvement, prioritize investments, benchmark against peers, and foster a culture of continuous improvement.
Ethics 1st AI Alliance.
Become a Member and get a Seat on the Ethics 1st AI Allianceᵀᴹ!
By bringing together stakeholders from across industries, the alliance will help in fostering discussions, share best practices, and develop a shared understanding of what constitutes ethical data and AI practices.
This collective effort will help in creating a comprehensive set of guidelines and standards that companies can follow to ensure they are using data and AI ethically.
The DataEthics4All Foundation will provide the leadership and expertise needed to facilitate the alliance’s efforts.
The foundation will work to bring together stakeholders from different sectors and disciplines to ensure a broad and diverse perspective on ethics in data and AI.
It will also provide a forum for discussions on emerging ethical challenges related to data and AI, as well as a platform for sharing best practices and tools for ethical data and AI management.
By participating in the Ethics 1st AI Assessment, The Alliance will help companies to earn customer trust, employee trust, and more.
Ethics 1st AIᵀᴹ = Compliance + Trust
A company that demonstrates a commitment to ethical data and AI practices will be more likely to attract and retain customers and partners who value privacy and security.
Additionally, employees are more likely to trust and be loyal to a company that prioritizes their privacy and security.
The Ethics 1st AI MMIᵀᴹ will also help companies to reduce the risk of legal and reputational damage by ensuring that they are complying with relevant laws and regulations and upholding ethical standards.
In summary, DataEthics4All Foundation’s Ethics 1st AI Allianceᵀᴹ will be a powerful force for building a more ethical and trustworthy data and AI ecosystem and thereby an Ethics 1st Data and AI World!
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