In 2024, we will witness the proliferation of synthetic data across industries.

In 2023, companies experimented with foundational models, and this trend will continue. Organizations see it as an emerging force to reshape industries and change lives. However, the ethical implications can't be overlooked.

What else are we predicting for 2024? Find out.

Let’s explore some industries I think synthetic data generation could enhance in 2024. We’ll also look at the ethical considerations accompanying this journey.

1. Health care: Personalized treatment and ethical data handling

Synthetic data is positioned to make a difference in health care by offering the potential for personalized treatment plans and improved analysis of medical images. For instance, medical researchers could generate synthetic medical images to augment training datasets for medical imaging algorithms, reducing the need for real-world patient data.

But we need to be careful. A model trained on biased data might recommend different treatment options for patients based on race, gender, or socioeconomic status. It's important that we make sure synthetic data models are fair and impartial.

2. Banking: Securing finances with synthetic data

In the financial world, the ability to generate synthetic data holds promise for fraud detection, creditworthiness assessments and tailored financial recommendations. Yet, the abundance of sensitive data necessitates a focus on robust data protection.

Safeguarding against unauthorized access, misuse and modification of synthetic data should be a priority in 2024. Hopefully, this will drive the development of capabilities that ensure the security and privacy of financial data, protecting the industry against breaches.

3. Life sciences: Accelerating drug discovery

Life sciences stand to gain a lot from the proliferation of synthetic data. From identifying novel drug targets to predicting interactions, synthetic data will help expedite drug discovery. However, transparency and reproducibility become important.

Generating this synthetic data needs to be transparent and reproducible, helping other researchers verify and replicate research findings. This will help ensure the safety and reliability of synthetic data models in life sciences applications.

Looking ahead to 2024

As organizations continue to embrace synthetic data generation, there must be a simultaneous commitment to ethics. The path forward will demand vigilance in ensuring fairness, impartiality and privacy for synthetic data to transform industries and do so responsibly. If used correctly, this technology will lead to positive societal changes in 2024.


About Author

Vrushali Sawant

Data Scientist, Data Ethics Practice

Vrushali Sawant is a data scientist with SAS's Data Ethics Practice (DEP), steering the practical implementation of fairness and trustworthy principles into the SAS platform. She regularly writes and speaks about practical strategies for implementing trustworthy AI systems. With a background in analytical consulting, data management and data visualization she has been helping customers make data driven decisions for a decade. She holds a Masters in Data Science and Masters in Business Administration Degree.

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