Upravljanje s podatki v dobi umetne inteligence

Prenos, obdelava in shranjevanje podatkov so v jedru elektronskih komunikacij že od njenih začetkov. Vloga podatkov se je v zadnjih desetletij močno spremenila. Najhitreje rastoča podjetja v zadnjem desetletju so platforme, ki praktično nimajo fizične infrastrukture in so osnova za njihovo delo s podatki. Poleg poslovnega koncepta so podatki o uporabnikih njihovo največje bogastvo. Mnenje uporabnikov, realno ali pristransko, se hitro in enostavno širi po socialnih omrežjih in v veliki meri določa njihove poslovne rezultate. Na drugi strani so nove tehnologije za zbiranje podatkov te podatke obogatile in razvoj umetne inteligence omogoča njihovo učinkovito uporabo. Občutljivost teh podatkov je presegla vsa pričakovanja in postavila nove pravne in etične zahteve za njihovo zbiranje, prenos in shranjevanje. Ta ista inteligenca je namreč uporabna tudi za deanonimizacijo podatkov in ciljno oglaševanje. Jezikovni modeli na podlagi generativnih modelov, kot je ChatGPT, so naredili velik korak k uporabnosti podatkov, v smer k uporabnikom, saj so premostili luknjo med klasičnimi rezultati strojnega učenja in uporabniki. Nujna posledica tega razvoja je dejstvo, da umetna inteligenca na podatkih socialnih omrežjih omogoča izjemen vpliv na družbena dogajanja.
Tema delavnice Upravljanje s podatki v dobi umetne inteligence je torej v jedru tehnološkega, poslovnega in družbenega dogajanja. Dotika se vseh elementov komunikacijskih tehnologij, od zbiranja in hrambe podatkov do njihove uporabe na posameznih področjih. Uporabnost podatkov in tehnologij ter izzivov v prihodnosti na področjih, kot so oskrba starejših, zdravstvo, logistika, poučevanje in drugo je glavna tema 39. delavnice VITEL.
Vpeljava programsko določenih rešitev na novo postavlja temelje upravljanju s podatki, saj je dostopnost do občutljivih podatkov zelo razširjena. Na drugi strani je povezanost tehnološkega razvoja in razvoja pravne ureditve ter etičnih vodil ključna za uspešnost uporabe tehnologij v praksi. Evropska komisija za projekte, ki vključujejo testiranja s končnimi uporabniki, zahteva imenovanje etičnih svetovalcev, ki so upravičen projektni strošek.
Kot vedno so tudi zadnje velike tehnološke spremembe prinesle nove zahteve in zatresle razvoj vseh vpletenih tehnologij, od razvoja avtonomnih vozil do razvoja omrežij 5G z dovolj nizkimi zakasnitvami. Posledično se vsi deležniki soočajo z novimi izzivi, ki so v veliki meri povezani z zbiranjem, hrambo in uporabo podatkov, zasebnostjo uporabnikov ter mnenjem uporabnikov. Hkrati je družbena odgovornost nosilcev razvoja tehnologije na visoki ravni.

Na delavnici smo naslovili naslednje izzive na področju podatkov in umetne inteligence:

  • trendi in vloga podatkov pri družbenem razvoju,
  • vloga podatkov pri razvoju umetne inteligence,
  • podatkovna skladišča in napredne storitve,
  • podatki in situacijsko zavedanje pametnih sistemov,
  • podatki in varnost,
  • podatki in omrežja 5G,
  • energijski vidiki hrambe, prenosa in varovanja podatkov,
  • podatki in razvoj strojne opreme,
  • podatki in upravljanje industrijskih sistemov,
  • podatki v zdravstvenih sistemih,
  • podatki na področju poučevanja in učenja,
  • podatki in pametni dom,
  • podatki in digitalni dvojčki,
  • podatki in odprta znanost,
  • pravni vidiki varovanja občutljivih podatkov.

Data Management in the Age of Artificial Intelligence

The transmission, processing and storage of data have been at the core of electronic communications since its beginnings. The role of data has changed dramatically in recent decades. The fastest growing companies in the last decade are platforms that have practically no physical infrastructure and the basis of their work is data. Apart from the business concept, the data about their users is their greatest asset. The opinion of their users, real or biased, spreads quickly and easily through social networks and largely determines their business results. On the other hand, new data collection technologies have enriched this data and the development of artificial intelligence enables its effective use. The sensitivity of this data exceeded all expectations and set new legal and ethical requirements for its collection, transfer and storage. This same intelligence is also useful for data de-anonymization and targeted advertising. Linguistic models based on generative models such as ChatGPT have taken a big step towards the usability of data towards users by bridging the gap between classical machine learning results and users. A necessary consequence of this development is the fact that artificial intelligence on the data of social networks enables an extraordinary influence on social events.
The theme of the workshop Data Management in the Age of Artificial Intelligence is therefore at the core of technological, business and social developments. It touches all elements of communication technologies, from the collection and storage of data to their use in individual fields. Thus, the state of usability of data and technologies and future challenges in areas such as care for the elderly, healthcare, logistics, teaching and others is an important element of this year’s workshop. The usefulness of the information at the workshop remains among its important goals.
The introduction of software-defined solutions redefines data management, as access to sensitive data is expanded. On the other hand, the connection between technological development and the development of legal regulation and ethical guidelines is key to the successful use of technologies in practice. For projects involving end-user testing, the European Commission requires the appointment of ethical advisors, who are eligible project costs.
As always, the latest major technological changes have brought new demands and shaken up the development of all the technologies involved, from the development of autonomous vehicles to the development of 5G networks with sufficiently low latencies. As a result, all stakeholders face new challenges, which are largely related to the collection, storage and use of data, user privacy and user opinion. At the same time, the social responsibility of the carriers of technology development is at a high level.

At the workshop the following challenges in the field of data and artificial intelligence has been addressed:

  • trends and the role of data in social development,
  • the role of data in the development of artificial intelligence,
  • data warehouses and advanced services,
  • data and situational awareness of smart systems,
  • data and security,
  • data and 5G networks,
  • energy aspects of data storage,
  • transmission and protection,
  • data and hardware development,
  • data and management of industrial systems,
  • data in health systems,
  • data in the field of teaching and learning,
  • data and smart home,
  • data and digital twins,
  • data and open science,
  • legal aspects of protecting sensitive data.