In the race for innovation, efficiency and market share, organisations are increasingly turning to AI. Relying heavily on AI can pose commercial and reputational risks that can arise when AI models rely on limited, poor-quality or biased data.
More and more organizational and societal exposure to AI bias, lack of trust or unfairness of some AI algorithms make the front page, emphasizing the need for guidance and action to be taken to ensure the AI adoption happens in a responsible manner.
Fairer and more accurate AI decision making outcomes have been a priority for the Synthesized team and we're honoured to be recognised as a Gartner Cool Vendor in AI Governance and Responsible AI for 2021.
Gartner's assessment of Synthesized notes the strength of our platform in using AI and GANs to generate synthetic data for the purposes of mitigating data bias and improving the training of AI models.
Gartner says “Organisations that are coming under increasing security to ensure their AI models are performing within legal and ethical bounds when it comes to bias and fairness should consider Synthesized”.
They added that our solution is a good fit for all interested parties in an organization, including AI developers, data scientists, privacy and security staff, legal advisers, and risk managers, line of business leads, compliance officers, responsible for AI that identifies and mitigates hidden biases from their AI systems.
But What Is a Cool Vendor?
According to Gartner, the three elements of a Cool Vendor are defined as:
- Innovative — Enables users to do things they couldn’t do before.
- Impactful — Has or will have a business impact, not just technology for its own sake.
- Intriguing — Caught Gartner’s interest during the past six months.
To set the scene, here are some key statistics worth highlighting from the Gartner report:
- By 2023, all personnel hired for AI development and training work will have to demonstrate expertise in responsible development of AI.
- By 2024, 60% of the data used for the development of AI and analytics solutions will be synthetically generated.
- By 2025, the concentration of pre-trained AI models among 1% of AI vendors will make responsible AI a societal concern.
- Through 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance.
Our Approach to Bias & Responsible AI practices
We’ve recently open-sourced Fairlens — our open-source bias and fairness toolset (Python library) by inviting developers across the globe to try it in their own workflows, and help develop new features to tackle fairness in machine learning and algorithmic bias. Bias identification and remediation features support model development and collaboration across organizations without sacrificing data privacy.
With Synthesized you can:
- Detect automatically hidden biases across protected attributes such as age, gender, race
- Generate reporting on all detected biases and correlations within the dataset
- Generate bias-free and high quality synthetic data
- Visualize the distribution of a variable with respect to different sensitive demographics, or a correlation heatmap
How Will Synthesized Data Products Affect the Development of AI?
“By 2024, 60% of the data used for the development of AI and analytics solutions will be synthetically generated”
Gartner comments ”Organisations that require both high-quality data assets and need granular control over their data products should consider Synthesized”.
Synthesized creates performance optimized data products that are served via APIs and data marts for analytics, testing and data science. The optimization applied to data is all stored on the system and can be shared with the team while data scientists, data analysts and test engineers maintain ownership of the data.
A principal challenge with many data augmentation tools and platforms in the market is that they sacrifice data utility in the name of privacy. With Synthesized, data privacy and data utility are no longer mortal enemies. In a recent report we assessed the data quality of the synthetic data against an original credit dataset the data was generated from.
Privacy at the Very Core
"Data and analytics leaders who need to collaborate on AI models internally and with other organizations, but are inhibited from doing so because of privacy and data leakage concerns should consider Synthesized."
Synthesized places data privacy and security at the very core of creating highly valuable and bias free data products. Synthesized creates fully shareable data products that are GDPR, GRPA, HIPAA AND CCPA compliant whilst enabling data scientists to collaborate on:
- Reshaping and data manipulation
- Model training with unlimited new volumes of data generated in minutes
These are only some of the report highlights coupled with a closer look at those specific innovations that are already making a difference. I invite you to access the full version on the Gartner page.
We’re not only honoured by Gartner’s recognition, but even more energised and excited to continue our journey in developing the DataOps tools for making data both available and valuable to developers and bias free and secure for everyone.
If interested to have a chat with our data scientists, reach out through Contact Sales.
More to come,
Team Synth
