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Drawing from ethical concerns raised by communities of machine learning developers and considering predictive analytics’ very short-term predictions, several futures studies techniques are examined to offer some insights about possible bridges between machine learning and foresight. This review develops three main sections: (1) a brief explanation of central concepts, such as big data, machine learning, and artificial intelligence, hopefully not too simplistic but readable for larger audiences; (2) a discussion about ethical issues, such as bias, discrimination, and dilemmas in research; and (3) a brief description of how futures studies could address ethical dilemmas derived from different time horizons among machine learning immediate results, forecasting short-term predictions, and foresight long-term scenarios.
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Stored only when both papers are in the corpus — 16 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.