“ Data Revolution, preparing for the digital revolution ” is the title of the conference which will take place on Friday 31 May, from 9.30 am, at Sa Manifattura in Cagliari (first appointment of the event promoted by the Smart Companies for Smart Cities project), an initiative of the Apply company, financed by Sardegna Ricerche.

Exceptional speaker will be Donatella Taurasi, professor at the Haas School of Business at Berkeley University of California.

Professor, what is your CV?

«I was born in a small village in the green Irpinia, which I left at the age of 19 to undertake studies in Finance at the University of Bologna. During my PhD, I visited several universities abroad, including NYU Stern School of Business and Haas School of Business in California. These experiences were very formative, and the proximity to Silicon Valley soon involved me in the world of data and data science. During this time I discovered a great passion for teaching and, after my doctorate, I enthusiastically accepted the offer to join the faculty of the Haas School of Business. Since then, I have taught several courses, all featuring a strong focus on data and technology. I currently hold the role of Data Science Officer at Lumen Global Investments and am part of several advisory boards. My passion has always been to bridge the gap between technical and non-technical within companies. For this reason I am particularly proud to offer my experience and collaborate with startups such as DataMasters, the Italian AI Academy for training in Artificial Intelligence, Machine Learning and Data Science. My future is certainly oriented towards initiatives that will continue to fill this gap."

What does Data Culture mean?

«I believe it is the heart of any Artificial Intelligence initiative. It is a concept often underestimated by companies and organizations globally. We are well beyond the days of collecting data just for the sake of collecting it. We must free ourselves from referring to data with a capital letter D and start using it for what it is: a tool for an end."

What end?

«Making very high quality decisions that create value, at any level and in any context. The first step towards this goal is to cultivate data culture within our organizations, whether public, private or otherwise. Data culture refers to the adoption of practices and attitudes that enhance the use of data within an organization. This means fostering an environment where decisions are based on accurate and relevant data, and where all employees, regardless of their role, understand its importance and know how to use it effectively. A strong data culture promotes transparency, innovation and trust in data-driven analytics."

And Data Governance, what does it mean?

«When we use AI, especially Generative AI, any risk, be it bias, discrimination, hacking or an underperforming model, is amplified to levels that were unthinkable until a few years ago. The variable we can control more than anything else in the context of AI models is the input, i.e. the data. We absolutely need to focus on the quality of the data we use to train AI models. Data Governance, which I would call AI Governance to cover the entire process, is a key aspect that needs to be proactively cultivated in organizations and not just seen as a compliance exercise for regulators. Data Governance is the set of processes, policies, standards and metrics that ensure the effective and secure use of data within an organization. This includes managing data quality, protecting sensitive data, complying with regulations and defining responsibilities in various aspects of data management. Good data governance helps ensure that data is accurate, accessible and protected."

What are the challenges that companies face in developing an effective strategy in this sector?

«I know that many companies see the implementation of AI models as a challenge, but I believe they should see it as a great opportunity instead. Not equipping themselves to exploit it in their favor would be the digital equivalent, hand it to me, of shooting themselves in the foot. Starting from executives up to the entire hierarchical ladder, everyone in the company has the responsibility to understand the role of these tools, supported by quality data, in improving our decisions. Furthermore, this innovative process will allow us to review metrics and processes. Companies will certainly need to invest in staff training, ensuring that employees acquire the technical and non-technical skills needed to use data effectively. This step will help create an organizational culture that values the use of data and puts data at the center of every business decision. Every single company will need to ensure that they work with data that is of the highest quality (accurate, complete and up-to-date), secure (protected from unauthorized access and breaches) and accessible."

We talk about Artificial Intelligence every day, in which fields can it have concrete application and improve our everyday lives?

«Artificial Intelligence can improve our lives in many fields. In healthcare, it can offer faster and more accurate medical diagnoses, as well as personalized medicine. In transportation, it can lead to autonomous vehicles, traffic optimization and improvements in logistics. In the financial sector, AI can facilitate predictive analytics, fraud detection and investment management. In education, it can personalize learning, provide virtual tutors, and analyze student performance. Furthermore, AI can revolutionize customer service, predictive maintenance, automation of production processes and supply chain optimization. These are just a few examples, but the applications of AI go far beyond. We will certainly see (and are already seeing) interesting applications in data-rich sectors or in contexts where there has always been a strong vocation for data collection, especially through experiments."

But Artificial Intelligence - in the collective imagination - also does silly things, like putting glue in pizza or petrol in spaghetti...

«Artificial Intelligence is not perfect and can make mistakes, especially when it is not trained correctly or when the training data is of low quality. However, with good data governance and careful human oversight, much of this "nonsense" can be avoided. It is important to remember that AI is a tool and its effectiveness depends on how it is developed and implemented."

Do you think that young people in Italy are training sufficiently to face this "revolution", are Italian universities ready?

«Italian universities are making progress in integrating Artificial Intelligence into their study programs, but there is still a lot of work to do. It is crucial that academic institutions increase the offering of specific courses in AI, data science, statistics and programming, and that they collaborate with industries to ensure that curricula are relevant and up-to-date. Continuous training and learning are also essential to prepare young people for future challenges."

And in the United States?

«In the United States, many universities are already at the forefront of teaching AI and data science, with dedicated programs and collaborations with leading technology companies. However, there is a disparity between different institutions and regions. Elite universities offer excellent training opportunities, but it is important that these resources are also available in less prestigious universities and disadvantaged communities."

What do you think of the European Parliament's recent AI Act?

«The EU has moved much more decisively than the United States towards the codification of AI regulations. The European Parliament's AI Act represents a significant step towards regulating Artificial Intelligence to ensure its safe and ethical use. This act aims to create a clear regulatory framework that protects citizens' rights and promotes responsible innovation. The AI Act plays a crucial role in ensuring legal certainty, facilitating investment and innovation, and in developing a single market for AI, preventing market fragmentation within the EU. However, it is crucial that such regulations do not stifle innovation, but guide it in a direction that maximizes social and economic benefits. A balance between regulation and flexibility is needed to adapt to rapid technological evolutions."

What advice do you give to businesses and institutions?

«My advice to companies is to be proactive rather than reactive. The regulator must intervene in case of serious violations, especially in the privacy field. If companies implement processes that ensure these models work for the common good, in a transparent and accountable way, I believe the right balance can be found between regulation and innovation. I advise the regulator to prioritize communication with the various stakeholders before aggressively codifying a reality that is still in full development and about which we are still learning a lot."

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