Electronic Resource

Article - Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges Vol. 13, No. 12 7082

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The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large datasets
and requires a continuous supply of high-quality data. However, using data for AI is not without
challenges. This paper comprehensively reviews and critically examines the challenges of using data
for AI, including data quality, data volume, privacy and security, bias and fairness, interpretability
and explainability, ethical concerns, and technical expertise and skills. This paper examines these
challenges in detail and offers recommendations on how companies and organizations can address
them. By understanding and addressing these challenges, organizations can harness the power of AI
to make smarter decisions and gain competitive advantage in the digital age. It is expected, since
this review article provides and discusses various strategies for data challenges for AI over the last
decade, that it will be very helpful to the scientific research community to create new and novel ideas
to rethink our approaches to data strategies for AI.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

006.3 ALD r

Penerbit

: MDPI (Multidisciplinary Digital Publishing Institute).,

Deskripsi Fisik

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Bahasa

English

ISBN/ISSN

2076-3417

Klasifikasi

006.3 ALD r

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

Vol. 13, No. 12 7082

Subjek

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Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

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