Business Leaders Convene at Córdoba to Discuss Generative AI and Data Management
The Faculty of Economics and Business at Loyola University orchestrated a significant business meeting at the Real Circulo de la Amistad in Córdoba, focusing on the pivotal aspects of generative artificial intelligence and effective data management.
The key discourse at the event was delivered by Susana Andújar, a notable alumnus and a leading Partner in Digital Business Development for Customer Transformation at IBM Consulting iX. Andújar elucidated her comprehensive outlook on how the advent of generative AI transcends the realm of algorithmic advances and hardware improvements. She emphasized the foundational role of data collection, management, and application in augmenting the AI’s creative and operational capabilities.
The conversation went beyond technical enhancements, tackling the emerging challenges and prospects concerning ethical standards, privacy concerns, and fairness within the scope of AI utilization.
As part of a deeper exploration into the topic, a panel of experts will engage in discussions around 11:30 am, directed by the esteemed Rector of Loyola University, Fabio Gómez-Estern. The expert panel includes distinguished professionals like Luis Olmo Ferrete, a Manager specializing in Data & AI Strategy at Capgemini Invent, and José Ángel Pérez, a Senior Partner for NTT Data overseeing operations in Andalusia, the Canary Islands, and Extremadura.
Relevant to the topic of Generative AI and Data Management, here are some additional facts:
– Generative AI refers to the type of artificial intelligence capable of creating content, such as text, images, audio, and video, that can be comparable to that made by humans. It includes technologies like Generative Adversarial Networks (GANs), transformer models, and variational autoencoders.
– Data management is crucial for AI because the quality and structure of data can significantly impact the performance and outcomes of AI algorithms. Effective data management practices include data governance, data quality assurance, and the implementation of robust data infrastructure.
– IBM Consulting iX, where Susana Andújar works, is the business design arm of IBM Global Business Services, focusing on digital transformation through technologies like AI and cloud computing.
The most important questions associated with Generative AI and Data Management include:
– How can generative AI be integrated ethically and responsibly in business practices?
– What are the best practices for managing the vast amount of data needed to train generative AI models?
– What are the implications of generative AI on data privacy and user consent?
Key challenges or controversies involve:
– Ethical considerations: Ensuring that generative AI is not used to create misleading or harmful content, such as deepfakes.
– Privacy concerns: Safeguarding the privacy of individuals whose data may be utilized to train AI systems.
– Bias and fairness: Addressing the potential biases in AI models that can perpetuate or amplify societal inequalities.
Advantages and disadvantages of generative AI include:
– Advantages:
– Creativity and productivity: Generative AI can aid in creative processes, automating and enhancing content creation.
– Data utilization: It can turn vast datasets into insights, contributing to informed decision-making.
– Customization: Generative AI can create personalized content tailored to individual preferences.
– Disadvantages:
– Quality control: As generative AI creates content autonomously, monitoring quality and accuracy is challenging.
– Ethical risks: There is a potential misuse for manipulative purposes, including creating fake news or propaganda.
– Job displacement: The automation of content generation may impact jobs in creative industries.
For further information about generative AI, ethical AI, and data management, visitors may consult the following resources:
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