Appen, a global leader in high-quality training data for machine learning systems, has partnered with the World Economic Forum to design and release standards and best practices for responsible training data when building machine learning and artificial intelligence applications. As a World Economic Forum Associate Partner, Appen will collaborate with industry leaders to release the new standards within the “Shaping the Future of Technology Governance: Artificial Intelligence and Machine Learning” platform, which enables a global footprint and guidepost for responsible training data collection and creation across countries and industries.
The standards and best practices for responsible training data aim to improve quality, efficiency, transparency, and responsibility for AI projects while promoting inclusivity and collaboration. The adoption of these standards by the larger technology community will increase the value of – and trust in – the use of AI by businesses and the general public.
Modern AI applications largely depend on human-annotated data to train machine learning models that rely on deep learning and neural net technology. Responsible training data practices include paying fair wages and adhering to labor wellness guidelines and standards. Appen’s Crowd Code of Ethics, released in 2019.
“Ethical, diverse training data is essential to building a responsible AI system,” said CEO of Appen, Mark Brayan. “A solid training data platform and management strategy is often the most critical component of launching a successful, responsible machine learning powered product into production. We are delighted to share our 20+ years of expertise in this area, along with our Crowd Code of Ethics, with the World Economic Forum to accelerate standards and responsible practices across the technology industry.”
A key focus of the partnership will bring together leaders in the AI industry to:
- Contribute to the Human-Centered AI for Human Resources project
- Empower AI leadership with a C-Suite Toolkit and Model AI Governance Framework
“Getting access to large volumes of responsibly-sourced training data has been a longstanding challenge in the machine learning industry,” said Kay Firth-Butterfield, Head of AI and Machine Learning at the World Economic Forum. “The industry needs to respond with guidelines and standards for what it means to acquire and use responsible training data, addressing topics ranging from user permission, privacy, and security to how individuals are compensated for their work as part of the AI supply chain. We look forward to working with Appen and our multi-stakeholder community to provide practical guidance for responsible machine learning development around the world.”
Join industry leaders on October 14th for Appen’s annual Train AI conference providing leaders with the confidence to launch AI beyond pilot and into production. A curated collection of topics will teach how to successfully scale AI programs with actionable insights and get to ROI faster. Kay Firth-Butterfield will be the keynote speaker presenting on the importance of responsible AI practices and the tools available to leaders to ensure that ethical standards are being met.