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Generative AI, one of the subfields of Artificial Intelligence popularized in recent years where machines create the content based on existing information, is bringing significant changes to industries by making it possible for machines to create texts, images, and even music.
However, everyone knows that using any brilliant scientific invention itself requires compliance with ethical standards and requirements. In this article, we examine the generative AI technologies of SAS while addressing its responsibility for its AI applications.
Generative AI creates new data that looks like the training data by applying algorithms. This encompasses the production of life-like images, text flow, and even the most intricate designs. Generative AI can be applied in almost all sectors for ideas generation and in the research field, art and even in marketing.
Although intended as a way to automize human interaction, the use of generative AI needs to be done with a great caution as is possible to prevent such ethical issues.
SAS is a firm dealing in analytics and based in North Carolina and is one of the world’s leading companies when it comes to its strong commitment to the development of AI and, at the same time, a high level of adherence to ethical norms.
SAS talks about Responsible AI intending to do no harm and do a lot of good, with an emphasis on developing and implementing AI solutions that only have positive impacts on society, while addressing key criteria such as transparency, fairness, accountability, and privacy.
European Parliamentary and the Government of India are eager to embrace a principle-based approach to ethical AI with SAS development and here are the key principles of this approach:
Transparency of AI is focused on explaining what the AI system is doing to achieve its goals and on how it takes its decisions. SAS further argues that AI should be ‘’interpretable’’ whereby the process by which the algorithm arrives at its conclusion is comprehensible to the end users. This is important to establish credibility and to ensure that artificial intelligence systems can be reviewed for equity and faulty returns.
This means that the AI has been trained in such a way that it treats everyone equally without imposing bias or prejudiced disadvantage to anyone. The company under review, SAS, strives to create models that are fair and non-bias. For this reason, implementing fairness checks and balances at the model development level is a notable achievement of SAS to ensure the development of fair AI systems that will be able to offer equal justice for all users.
The following are the major dimensions of accountability in AI; Chains of responsibility: They explain the line of responsibility of AI based systems for the actions that they take and the decisions made on their behalf. SAS also stresses the need to have proper human control over usage of AI and that a proper check and balance system should always be present for an AI system and the people who launched it.
The following are the major dimensions of accountability in AI; Chains of responsibility: They explain the line of responsibility of AI based systems for the actions that they take and the decisions made on their behalf. SAS also stresses the need to have proper human control over usage of AI and that a proper check and balance system should always be present for an AI system and the people who launched it.
Data privacy is one of the tenets of good and sound artificial intelligence. SAS has measures in place to secure any data they will be processing especially if such data is sensitive in nature. Through a process of data anonymization and compliance with data protection norms, SAS has taken measures to prevent the generation of AI as a threat to privacy.
Thus, SAS has been at the forefront in the discovery and application of generative AI across different fields. Here are some key applications:
In healthcare, generative AI can be used to generate synthetic data for the analysis of patient records without compromising the patient’s privacy as it would help in the creation of new therapies. SAS and generative AI can build the simulation models of intricate biological systems, as well as benefit from drug development and create the patient-centric treatment plans.
Generative AI can be applied in the financial sector whereby, it will help determine fraudulent activity based on perceived transaction trends. The AI models in operation with SAS produce real-life-like transaction data to improve systems’ abilities to detect anomalies, in turn improving the detection of such fraudulent activities.
Advancements in generative AI can make marketing content more suitable through developing unique advertisements that reflect a consumer’s behavior. SAS uses generative AI to enhance marketing efforts, thus satisfying clients and, in turn boosting their sales.
In manufacturing, use of generative AI can be used to develop an improved variant of the product to be manufactured from the generated designs. SAS uses generative AI in reducing product development costs and time and thus, the company comes up with game changing manufacturing solutions.
First, the accountabilities include the idea that SAS should improve its AI solutions’ performance by regulating them constantly for compliance with ethical norms. Here are some strategies employed by SAS:
The company SAS said that it remains committed to the pursuit of lifelong learning and refinement of AI models to align with the ever-shifting ethical benchmarks and growth of emerging technologies. For example, this involves coming up with new methods of feeding new data and updating the systems from time to time as well as enhancing the algorithms.
SAS works with universities and other academic institutions, industry stakeholders, and regulatory agencies to create and drive the adoption of practices around the ethical use of AI. This ensures that the product developed by SAS is appropriate in terms of ethical practices and relevant policies.
It is also important for SAS to raise awareness of the current possibility of misuse of the technology among the users. Through education and support, SAS prepares users to be wise, and technologically proficient in Artificial Intelligence. This will help in optimizing possible benefits of artificial intelligence whilst also efficiently containing the probability of harms from artificial intelligence.
Further research and growth are still undergoing to bring in more advanced and ethical facilitation of generative AI in the SAS system for the future. Therefore, SAS is committed not only to exploring the frontiers of Sophisticated Applications of Generative AI but also to the safe practice of this technology.
Another important aspect is the updates that SAS makes to the AI solutions. The company implements and develops neural networks and other sophisticated machine learning algorithms into generative AI systems to increase their efficiency.
SAS is one of the active players promoting ethical AI principles that may help create norms and rules to support the safe use of SAAS AI solutions. These frameworks are also intended to help to regulate the use of AI.
SAS is looking for new ways and opportunities to apply more of the generative AI technology as it moves forward. Some of the areas where AI can be used, range from employment, mimicking scenarios to enhance training- to entertainment.
Generative AI has potential to change the existing and new trends of industries; however, its properly managed execution is mandatory so that it can serve the purpose of revolution in the given area without compromising the ethical norms.
Currently, SAS is among the pioneering companies in evaluating practical application of generative AI with a focus on transparency, fairness, accountability, and data protection standards. By following these concepts, SAS becomes the trendsetter leading to a world where AI can be creative and at the same time, moral.
In terms of definition, generative AI refers to the ability of algorithms to create new insights based on existing data. This includes the production of readable and impressive images as well as generation of coherent texts and intricate patterns among others.
SAS practices its AI responsibly through the principles of explainability, non-nondiscrimination, recognition of their governance, and data confidentiality. This include: explainability to ensure that the AI operating system and its decision is understandable; Fairness in that any outcome that the AI has arrived at cannot be discriminative; Supervised control that suggests there must always be human control and monitoring of any AI system; Data protection to ensure maximum protection of users’ information.
To answer this question, let us turn to the particular domains that can be enhanced with the help of Generative AI and SAS.
At SAS some of the areas that it uses generative AI are healthcare, finance, marketing, and manufacturing businesses. As such, the uses of synthetic data include conducting research using fake data, optimally designing products, and identifying fraud.
Responsible AI is crucial to ensure that all AI developments utilize the technology for the right reasons without posing dangers. Since it fosters trust; it provides fairness in the outcomes and preserves the privacy of individuals and groups; lastly, it lays down responsibilities of the creators of artificial intelligences and their systems.
