Multi-disciplinary Learning and Innovation for Professional Design of AI-Powered Services

Wärnestål, Pontus

doi:10.1007/978-3-031-06675-7_2

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Studi ini menyarankan dan memverifikasi lingkungan dan proses pembelajaran yang produktif dan efisien di mana perusahaan, departemen penelitian universitas, dan lembaga desain berkolaborasi untuk menghasilkan layanan bertenaga AI dan pada saat yang sama mengembangkan kompetensi mereka dalam AI dan desain yang berpusat pada manusia (Wärnestål, 2022). Penulis melihat peluang besar dalam penggunaan AI (artificial intelligenc) dalam pembelajaran Pendidikan agama Islam, karena pemanfaatan aplikasi kecerdasan buatan dalam pembelajaran pendidikan agama Islam (PAI) merupakan salah satu inovasi yang dapat meningkatkan kualitas dan efisiensi proses belajar mengajar.…”

Section: Beberapa Tantangan Dan Hambatan Yang Dialami Lembaga Pendidikanunclassified

Inovasi Penggunaan AI (Artificial Intelligenc) Dalam Pembelajaran Pendidikan Agama Islam di MAN 4 Persiapan Kota Medan

Lubis,

Naldi,

Reskina

et al. 2023

JBPI

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Era digital saat ini Inovasi penggunaan AI (Artificial Intelligence) dalam pembelajaran sangat dibutuhkan. Guru pendidikan agama Islam harus mampu melakukan inovasi pembelajaran. Tujuan penelitian adalah untuk menganalisis inovasi dan kendala penggunaan Artificial Intelligence dalam pembelajaran Pendidikan Agama Islam di MAN 4 Persiapan Kota Medan. Metode penelitian adalah kualitatif dengan pendekatan fenomenologi, Hasil penelitian ini menemukan inovasi penggunaan Artificial Intelligence di MAN 4 Persiapan Kota Medan menggunakan aplikasi e-learning Madrasah. Keunggulan aplikasi ini Melalui e-learning madrasah, guru dan siswa dapat melakukan video conference yang terintegrasi dengan siswa dan stakeholder tanpa batasan waktu dan gratis. Selain itu juga penilaian harian, quiz, penilaian akhir semester dapat dilakukan melalui ujian berbasis komputer yang langsung diolah menjadi nilai rapor. Kendala yang dihadapi dalam penguasaan aplikasi e-learning Madrasah 1). Lemahnya penguasaan teknologi oleh guru dan siswa 2). Beberapa siswa masih belum memiliki handpone atau komputer 3). Minimnya sosialisasi penggunaan aplikasi e-learning kepada guru dan siswa.

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Section: Beberapa Tantangan Dan Hambatan Yang Dialami Lembaga Pendidikanunclassified

Inovasi Penggunaan AI (Artificial Intelligenc) Dalam Pembelajaran Pendidikan Agama Islam di MAN 4 Persiapan Kota Medan

Lubis,

Naldi,

Reskina

et al. 2023

JBPI

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“…Of these three experiments, the commuter is the only experiment that not only focuses on the teach-learn capabilities of neural networks but also takes interaction and user experience design into account. This is a limitation of the work, as there are many challenges related to interactivity and interaction (Wärnestål, 2020;. The decision to not focus more on these challenges in this and the following research questions is based on how issues related to the use of neural networks are deemed more pressing at this stage.…”

Section: Rq 11 How Would a Hic-ml Approach Alter The ML System Design...mentioning

confidence: 99%

NEURAL NETWORKS IN CONTEXT: CHALLENGES AND OPPORTUNITIES A Critical Inquiry into Prerequisites for User Trust in Decisions Promoted by Neural Networks

Holmberg¹

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Artificial intelligence and machine learning (ML) in particular increasingly impact human life by creating value from collected data. This assetisation affects all aspectsof human life, from choosing a significant other to recommending a product for us to consume. This type of ML-based system thrives because it predicts human behaviour based on average case performance metrics (like accuracy). However, its usefulnessis more limited when it comes to being transparent about its internal knowledge representations for singular decisions, for example, it is not good at explaining why ithas suggested a particular decision in a specific context.The goal of this work is to let end users be in command of how ML systems are used and thereby combine the strengths of humans and machines – machines which can propose transparent decisions. Artificial neural networks are an interesting candidate for a setting of this type, given that this technology has been successful in building knowledge representations from raw data. A neural network can be trained by exposing it to data from the target domain. It can then internalise knowledge representations from the domain and perform contextual tasks. In these situations, the fragment of the actual world internalised in an ML system has to be contextualised by a human to beuseful and trustworthy in non-static settings.This setting is explored through the overarching research question: What challenges and opportunities can emerge when an end user uses neural networks in context to support singular decision-making? To address this question, Research through Design is used as the central methodology, as this research approach matches the openness of the research question. Through six design experiments, I explore and expand on challenges and opportunities in settings where singular contextual decisions matter. The initial design experiments focus on opportunities in settings that augment human cognitive abilities. Thereafter, the experiments explore challenges related to settings where neural networks can enhance human cognitive abilities. This part concerns approaches intended to explain promoted decisions.This work contributes in three ways: 1) exploring learning related to neural networks in context to put forward a core terminology for contextual decision-making using ML systems, wherein the terminology includes the generative notions of true-to-the-domain, concept, out-of-distribution and generalisation; 2) presenting a number of design guidelines; and 3) showing the need to align internal knowledge representations with concepts if neural networks are to produce explainable decisions. I also argue that training neural networks to generalise basic concepts like shapes and colours, concepts easily understandable by humans, is a path forward. This research direction leads towards neural network-based systems that can produce more complex explanations that build on basic generalisable concepts.

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What is Human-Centered about Human-Centered AI? A Map of the Research Landscape

Capel

Brereton

2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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Multi-disciplinary Learning and Innovation for Professional Design of AI-Powered Services

Cited by 3 publications

References 17 publications

Inovasi Penggunaan AI (Artificial Intelligenc) Dalam Pembelajaran Pendidikan Agama Islam di MAN 4 Persiapan Kota Medan

Inovasi Penggunaan AI (Artificial Intelligenc) Dalam Pembelajaran Pendidikan Agama Islam di MAN 4 Persiapan Kota Medan

NEURAL NETWORKS IN CONTEXT: CHALLENGES AND OPPORTUNITIES A Critical Inquiry into Prerequisites for User Trust in Decisions Promoted by Neural Networks

What is Human-Centered about Human-Centered AI? A Map of the Research Landscape

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