Essec\Faculty\Model\Contribution {#2506
#_index: "academ_contributions"
#_id: "16851"
#_source: array:26 [
"id" => 16851
"slug" => "16851-algorithms-trap-us-in-the-familiar-can-they-also-spark-breakthroughs"
"yearMonth" => "2026-08"
"year" => 2026
"title" => "Algorithms Trap Us in the Familiar. Can They Also Spark Breakthroughs?"
"description" => "LAZAR, M., LIFSHITZ, H., AYOUBI, C. et EMUNA, H. (2026). Algorithms Trap Us in the Familiar. Can They Also Spark Breakthroughs? <i>MIT Sloan Management Review</i>, 68(1), pp. 16-17."
"authors" => array:4 [
0 => array:3 [
"name" => "AYOUBI Charles"
"bid" => "B00270671"
"slug" => "ayoubi-charles"
]
1 => array:1 [
"name" => "Lazar Moran"
]
2 => array:1 [
"name" => "Lifshitz Hila"
]
3 => array:1 [
"name" => "Emuna Hen"
]
]
"ouvrage" => ""
"keywords" => array:8 [
0 => "Data"
1 => "AI"
2 => "& Machine Learning"
3 => "Innovation"
4 => "Innovation Strategy"
5 => "New Product Development"
6 => "AI"
7 => "& Machine Learning"
]
"updatedAt" => "2026-10-14 09:20:58"
"publicationUrl" => "https://doi.org/10.63383/yZKs2231"
"publicationInfo" => array:3 [
"pages" => "16-17"
"volume" => "68"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Most digital tools are designed for efficiency, not exploration — and that can stymie innovation. New research shows that standard algorithms channel team members toward popular, familiar information, leading them to independently converge on the same ideas. But the researchers uncovered a surprisingly simple fix: By using algorithms designed to surface diverse, uncommon information, domain experts can avoid “ideation bubbles” and generate ideas across entirely new solution spaces."
"en" => "Most digital tools are designed for efficiency, not exploration — and that can stymie innovation. New research shows that standard algorithms channel team members toward popular, familiar information, leading them to independently converge on the same ideas. But the researchers uncovered a surprisingly simple fix: By using algorithms designed to surface diverse, uncommon information, domain experts can avoid “ideation bubbles” and generate ideas across entirely new solution spaces."
]
"authors_fields" => array:2 [
"fr" => "Management"
"en" => "Management"
]
"indexedAt" => "2026-10-23T20:23:42.000Z"
"docTitle" => "Algorithms Trap Us in the Familiar. Can They Also Spark Breakthroughs?"
"docSurtitle" => "Journal articles"
"authorNames" => "<a href="/cv/ayoubi-charles">AYOUBI Charles</a>, Lazar Moran, Lifshitz Hila, Emuna Hen"
"docDescription" => "<span class="document-property-authors">AYOUBI Charles, Lazar Moran, Lifshitz Hila, Emuna Hen</span><br><span class="document-property-authors_fields">Management</span> | <span class="document-property-year">2026</span>"
"keywordList" => "<a href="#">Data</a>, <a href="#">AI</a>, <a href="#">& Machine Learning</a>, <a href="#">Innovation</a>, <a href="#">Innovation Strategy</a>, <a href="#">New Product Development</a>, <a href="#">AI</a>, <a href="#">& Machine Learning</a>"
"docPreview" => "<b>Algorithms Trap Us in the Familiar. Can They Also Spark Breakthroughs?</b><br><span>2026-08 | Journal articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://doi.org/10.63383/yZKs2231" target="_blank">Algorithms Trap Us in the Familiar. Can They Also Spark Breakthroughs?</a>"
]
+lang: "en"
+"_score": 9.023208
+"_ignored": array:2 [
0 => "abstract.en.keyword"
1 => "abstract.fr.keyword"
]
+"parent": null
}