24 Marzo 2017
Alcuni dei migliori professionisti del mondo della progettazione digitale si sono confrontati sulle implicazioni professionali della disciplina e sul suo impatto tra gli addetti ai lavori sia a livello organizzativo che progettuale.
Ospiti Elena Sara Cagnoni e Gigliana Orlandi (Whirlpool), Simone Di Somma (Innaas), Francesca A. Lisi (Università degli Studi di Bari + AI*IA), Guido Vetere (Cervelli nella vasca).
A moderare l’incontro Paolo Ciuccarelli (DensityDesign + Politecnico di Milano).
Organizzato dal Corso di Alta Formazione in User Experience Design.
The UX Talk: UX, Data & Artificial Intelligence event is set to explore the intersection of user experience design, data, and artificial intelligence. The event aims to bring together professionals from these fields to discuss and learn about the latest trends, best practices, and innovations in the realm of UX and AI. The objective of the event is to provide insights into how AI is shaping the future of user experience design and data analysis, and how professionals can leverage AI to create more engaging and personalized experiences for their users.
The event will cover various topics related to UX, data, and artificial intelligence, including data normalization, synthetic data generation, AI content generation, the use of AI in mobile app development (specifically with Flutter), natural language processing with Large Language Models (LLM), and the use of AI in chatbots and virtual assistants (such as Dialogflow and Firebase). Additionally, the event will explore the ethical implications of AI, including topics such as open AI and stable diffusion.
One of the key focuses of the event will be on the business use cases of artificial intelligence. AI is rapidly transforming the way businesses operate, and the event will showcase various innovative applications of AI in real-world business scenarios. One such use case is the use of AI for data normalization in a sales and marketing context.
In the world of sales and marketing, businesses have access to a huge amount of data, including customer information, sales figures, and marketing campaign performance metrics. However, this data is often stored in different formats and across multiple systems, making it challenging to consolidate and analyze effectively. This is where AI can play a crucial role.
By leveraging AI algorithms for data normalization, businesses can automate the process of standardizing and organizing their data, regardless of its original format. This allows for more accurate and comprehensive analysis, leading to better insights and informed decision-making. For example, AI-powered data normalization can help a sales team to identify trends in customer behavior, optimize their sales processes, and improve the targeting of their marketing campaigns.
Another business use case for AI is synthetic data generation for testing and training machine learning models. In many industries, the availability of real-world data for training and testing AI models is limited, especially in fields where privacy concerns or regulatory constraints are present. This is where synthetic data generation can fill the gap.
By using AI algorithms to create synthetic data that closely mimics real-world scenarios, businesses can ensure that their machine learning models are adequately trained and tested, even when real data is scarce. This can be particularly useful in industries such as healthcare, finance, and transportation, where access to sensitive and proprietary data is difficult. For example, in the healthcare industry, AI-generated synthetic data can be used to train and test diagnostic and predictive models, leading to improved accuracy and reliability in patient care.
Furthermore, AI content generation is another valuable use case for businesses. With the rise of digital marketing and content-driven strategies, the demand for high-quality and engaging content is higher than ever. However, creating such content at scale can be time-consuming and resource-intensive. AI can help alleviate this burden by automating the process of content generation.
Using AI-powered tools, businesses can create compelling and personalized content, such as product descriptions, social media posts, and email newsletters, at a fraction of the time and cost. This not only frees up human resources for more strategic tasks but also enables businesses to deliver tailored content to their audiences, ultimately driving engagement and conversion rates.
In summary, the UX Talk: UX, Data & Artificial Intelligence event offers a comprehensive exploration of the role of AI in shaping user experience design and data analysis. With a focus on practical business use cases, the event aims to equip professionals with the knowledge and insights necessary to leverage AI for creating more engaging and personalized experiences for their users.
Tagged: , POLI.design , Yoroom , Milano , Professionisti , Progettazione , Digitale , User , Experience , Design , Designer , UXD , USer Experience , Interface , UX , Whirlpool , Innaas , Università , UX Talk , Talk , Incontro , Studenti , DensityDesign , Politecnico , Politecnico Milano , Paolo Ciuccarelli , Data , Artificial Intelligence , AI