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What is AI TRiSM?

As AI automation is becoming increasingly popular across all industries, the concerns of risks associated with it has also increased. Lack of transparency, concentration of power, security risks, disinformation & lack of ethics are one of the common concerns of integration of AI in a business.
AI TRiSM is a set of solutions that enables businesses to proactively identify and eliminating the risks associated with AI models and applications, ensuring that AI systems are compliant, fair, and dependable and protecting data privacy.

Listed below are the ways to incorporate AI TriSM-
1.      Explainability-
This process allows AI mechanisms to be unambiguous and understandable to human users.
Explainable artificial intelligence (XAI) allows human users to comprehend and trace the results and output created by machine learning algorithms. The goal of XAI is to explain attributes and decision processes in ML algorithms

2.      ModelOps- ModelOps is the first cloud-native, enterprise-wide capability for managing all your production models. Other than ML it encompasses all models from inception to retirement.
By addressing three issues that are crucial to the success of your models: data quality, time to deployment, and model performance degradation, ModelOps focuses on the governance and the full life cycle management of all AI and decision models.

3.      Data anomaly detection- Data is the backbone of AI automation. Data anomaly detection keeps the integrity of AI systems intact by:
·        Mitigating errors and related to the training data.
·        Monitoring and correcting instances of model drift.

4.      Adversarial attack resistance-
In AI, the term "adversarial attack" describes the purposeful insertion of well-constructed input data into machine learning models to manipulate them. These attacks produce incorrect outputs or misclassifications by taking advantage of flaws in the models' decision-making processes.

5.      Data protection- The idea behind data protection is to use techniques and tools to safeguard and provide access to data in any situation. By using disk, tape, or cloud backup to securely store copies of the data that may be used in the case of data loss or interruption, storage technologies can be used to protect data.