#OpenAccess#research on #EdTech:
The most effective #LearningGames do more than simply impart knowledge.
They captivate learners, spark their curiosity and foster meaningful emotional connections.
👉They transform learning into an insightful experience.
https://t.co/ejC4aTsEhj
Featuring my latest article on explainable artificial intelligence (XAI)
👉This contribution is based on Prof. Camilleri’s latest research published through Technological Forecasting and Social Change!
@maltainde@elsevierconnect#AI#ExplainableAI#XAI https://t.co/Zizccdr4bj
This TFSC contribution🔓 advances a conceptual framework for the responsible implementation of XAI and offers practical guidelines that promote the interpretability of AI systems, whilst addressing their opacity, as well as their biased outcomes.
https://t.co/HbB0SCDgP5 #AI#XAI
🤔 Everyone talks about AI performance.
Few ask the real question:
Can your model explain itself?
Did you open the black box yet?
If your AI can’t explain its decisions, can you really trust it?
Learn on XAI:
https://t.co/oNHI1JQ5SD
https://t.co/7s8KxiBlr5 #XAI#Blackbox
#FreePDF: This research raises awareness on the important synergies between #gaming design elements & behavioral dimensions driving the users' engagement with #edutainment#apps.
It puts forward a robust theoretical framework that is empirically-grounded. https://t.co/nrcvVzjUVL
💡#OpenAccess Paper on #ExplainableAI (#XAI):
👉This research serves as a valuable resource for those aiming to move beyond black-box reliance toward more informed, responsible and accountable AI oversight.
🤨Read further: https://t.co/403XEiRYHi #AI#AIgov#ResponsibleAI#CSR
Delighted to share that @umMalta has featured my latest article, published by @Elsevier’s Technological Forecasting and Social Change (ABS 3; ABDC A).
This open access contribution is focused on explainable #ArtificialIntelligence (#XAI).
#AIgovernance https://t.co/O3ncWGqHHM
#OpenAccess paper on ExplainableAI (Published via #TFSC):
This contribution features a comparison matrix of XAI tools that specifies their key metrics, strengths, weaknesses/limitations and domain fit.
#EthicalAI#XAI#AIexplainability#FairAI#Blackbox https://t.co/qngUyTq4cB
This TFSC paper describes #XAI tools (e.g. #SHAP, #LIME, #ELI5) & platforms that offer concrete entry points for integrating #AI interpretability into workflows.
It outlines key metrics, strengths, limitations and domain suitability to support developers. https://t.co/muSZp4r80U
📣📣📣 #JustPublished my latest (sole authored) open-access🔓 article on #ExplainableArtificialIntelligence (#XAI).
👉It was accepted for publication through Technological Forecasting and Social Change (CS26.3; IF13.3; ABDC A; ABS 3) !
https://t.co/oNHI1JQ5SD
#BlackBox#AI
Study🔓 on #GenAI (#ChatGPT) via #TFSC: There are highly significant effects between source trustworthiness & performance expectancy from AI chatbots, as well as between perceived interactivity & intentions to its algorithm.
https://t.co/jlVOkLKk0H
#measures#technologyadoption
🤔 #OpenInnovation involves a high degree of trust and belief among collaborating partners.
👉 This notion suggests that companies benefit from the knowledge & capabilities of stakeholders, incl. of their human resources, as well of external participants. https://t.co/2OJXdfm5WW