AI Data Set Bias Training

As artificial intelligence (AI) continues to make inroads into the workplace, education, and training industry, it’s crucial to address potential biases arising from its use. AI bias can lead to unfair treatment, perpetuate existing inequalities, and hinder learning opportunities for students and professionals.

Bias in AI refers to systematic and unfair discrimination against certain individuals or groups based on data that reflects historical, social, or cultural prejudices.

Unbiasfy aims to train existing AI algorithms on diverse and inclusive data sets, representing different demographics, in the first instance gender.

Our solution

Data is the backbone of artificial intelligence (AI), and it plays a crucial role in shaping the performance and fairness of AI systems. However, when data sets are biased, they can lead to skewed results, reinforcing existing inequalities and perpetuating unfair outcomes.

Addressing bias in AI data sets is an important step towards creating more equitable and reliable AI systems. Unbiasfy is here to help you and your organization implement the above points, so you can positively be part of the ‘future of work’ and harness the power of AI for the benefit of all.

Technology Integration

Unbiasfy uses RAG technology to enhance LLMs with bias-specific data. AI bots generate new data, collaborating with influencers and women-led companies

Understand and Diversify Data Sources

Assess data sources for biases and incorporate diverse data to represent various demographics and perspectives. Leverage WiBT’s network for comprehensive data collection

Expert Collaboration

Engage domain experts to identify and address potential biases, ensuring AI accuracy and fairness

Pre-processing and Fairness

Apply techniques like data cleaning and normalization. Use fairness metrics to evaluate the impact on different demographic groups

Incentivize and Improve

Encourage data contributions with blockchain rewards and continuously monitor and improve based on new data and feedback.

Why now?

AI Data Governance

With vast amounts of data being generated and analyzed by AI systems data governance has become more critical than ever, ensuring the responsible use and management of data is essential for privacy, security, and ethical considerations.

Accuracy, Robustness, and Cybersecurity

As artificial intelligence continues to advance and permeate various aspects of our lives, ensuring the accuracy, robustness, and cybersecurity of AI systems is crucial for maintaining trust and achieving desired outcomes

Transparency Obligations

Transparency in AI involves disclosing information about AI systems, their decision-making processes, and the data they use.By embracing transparency obligations, organizations can build trust with users, foster ethical AI development, and promote a responsible approach to AI implementation.

Prohibited Practices

Prohibiting harmful AI practices is essential for safeguarding human rights, promoting fairness, and ensuring that AI is developed and used for the betterment of society.