牛の取り扱いと屠殺の評価における人工知能とヒトの観察力の比較

#tbcss .wpv-pagination-nav-links[data-toolset-views-view-pagination-block="43ce1138731801103cfd3748a3dd45ff"] { text-align: left;justify-content: flex-start; } #tbcss .tb-field[data-toolset-blocks-field="cc518238b14e73a1f77d592867f7a5b0"] { font-size: 11px;text-align: left;color: rgba( 1, 102, 180, 1 ); }  .tb-container .tb-container-inner{width:100%;margin:0 auto} #tbcss .wp-block-toolset-blocks-container.tb-container[data-toolset-blocks-container="3ba5f3115280d883e80356a318880859"] { background: rgba( 243, 243, 243, 1 );padding: 25px; } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row } #tbcss .tb-field[data-toolset-blocks-field="dc2c6421f105727557deb0125a823e19"] { font-size: 16px;text-align: left;color: rgba( 1, 102, 180, 1 ); }  #tbcss h5.tb-heading[data-toolset-blocks-heading="01751bc11cd861416022fd857afaa68d"]  { font-size: 14px;text-align: left; }  #tbcss h5.tb-heading[data-toolset-blocks-heading="01751bc11cd861416022fd857afaa68d"] a  { color: rgba( 1, 102, 180, 1 );font-size: 20px; } #tbcss h5.tb-heading[data-toolset-blocks-heading="01751bc11cd861416022fd857afaa68d"] a:hover  { color: rgba( 91, 210, 216, 1 );font-weight: bold; } #tbcss h5.tb-heading[data-toolset-blocks-heading="01751bc11cd861416022fd857afaa68d"] a:active  { color: rgba( 255, 87, 0, 1 ); } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] { padding-bottom: 30px;grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } #tbcss .wpv-custom-search-filter-submit[data-toolset-views-custom-search-submit="a3b8d1c4c4e77dad388dd05dadcab741"] { text-align: left;text-align: center; } #tbcss .wpv-custom-search-filter-submit[data-toolset-views-custom-search-submit="a3b8d1c4c4e77dad388dd05dadcab741"] .wpv-submit-trigger { background-color: rgba( 1, 102, 180, 1 );padding: 20px 30px 20px 30px;border: 0px solid rgba( 0, 0, 0, 1 );border-radius: 4px;text-align: center; } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="fa5236e2fdaaa5caca8b85a50e260df3"] label, #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="fa5236e2fdaaa5caca8b85a50e260df3"] .editor-rich-text__editable { font-size: 16px;color: rgba( 1, 102, 180, 1 ); } #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="418a28d80d3cab284a6ac605d4e3bb0e"] label, #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="418a28d80d3cab284a6ac605d4e3bb0e"] .editor-rich-text__editable { font-size: 16px;color: rgba( 1, 102, 180, 1 ); } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="1bec8e2caa4d6da8a3027f92ce0fd30a"] { display: flex; } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="1bec8e2caa4d6da8a3027f92ce0fd30a"] p { font-family: Allan;font-weight: regular; } #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="f4215e6ab06bcb05659a9395eb3d62da"] label, #tbcss .wpv-custom-search-filter[data-toolset-views-custom-search-filter="f4215e6ab06bcb05659a9395eb3d62da"] .editor-rich-text__editable { font-size: 16px;color: rgba( 1, 102, 180, 1 ); } #tbcss h4.tb-heading[data-toolset-blocks-heading="083d6c11bd8364f302177e770c60f00f"]  { color: rgba( 1, 102, 180, 1 );text-align: left;border-radius: 0;padding: 5px 10px 5px 10px;margin-bottom: 15px;border-left: 8px solid rgba( 1, 102, 180, 1 ); }  .tb-container .tb-container-inner{width:100%;margin:0 auto} #tbcss .wp-block-toolset-blocks-container.tb-container[data-toolset-blocks-container="05769b0e88876e509f5fc16ca0536c7f"] { padding: 25px; } #tbcss .wp-block-toolset-blocks-container.tb-container[data-toolset-blocks-container="05769b0e88876e509f5fc16ca0536c7f"] p { font-size: 14px;line-height: 16px; } #tbcss .tb-fields-and-text[data-toolset-blocks-fields-and-text="0d93f81d65efc83c0475b45aa8e529a8"] { font-size: 16px;font-weight: normal;line-height: 1em;letter-spacing: 1px;background-color: rgba( 249, 246, 246, 1 );padding: 10px;border: 0px solid rgba( 0, 0, 0, 1 ); } #tbcss .tb-fields-and-text[data-toolset-blocks-fields-and-text="0d93f81d65efc83c0475b45aa8e529a8"] p { font-size: 16px;font-weight: normal;line-height: 1em;letter-spacing: 1px; } @media only screen and (max-width: 750px) {  .tb-container .tb-container-inner{width:100%;margin:0 auto}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row }   .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="1bec8e2caa4d6da8a3027f92ce0fd30a"] { display: flex; }  .tb-container .tb-container-inner{width:100%;margin:0 auto}#tbcss .tb-fields-and-text[data-toolset-blocks-fields-and-text="0d93f81d65efc83c0475b45aa8e529a8"] { background-color: rgba( 247, 247, 247, 1 );border: 15px solid rgba( 246, 246, 246, 1 ); }  } @media only screen and (max-width: 599px) {  .tb-container .tb-container-inner{width:100%;margin:0 auto}.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } #tbcss .wpv-view-output[data-toolset-views-view-editor="f0ed38db9f0315948ea560b4ee0691ae"] .js-wpv-loop-wrapper > .tb-grid { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row }   .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } #tbcss .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f3b473ff6ddbba1d1168eb6e735d2314"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } #tbcss .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="1bec8e2caa4d6da8a3027f92ce0fd30a"] { display: flex; }  .tb-container .tb-container-inner{width:100%;margin:0 auto} } 

A Comparison of Artificial Intelligence and Human Observation in the Assessment of Cattle Handling and Slaughter

Lily Edwards-Callaway, Huey Yi Loh, Carina Kautsky, Paxton Sullivan

2025/05/03

https://doi.org/10.3390/ani15091325

論文概要

屠畜場（食肉処理施設）では、動物の取り扱いを評価するためにライブ検査、リモートビデオ検査、人工知能（AI）を用いた技術など様々なツールが使用されている。本研究では、屠畜場での牛の取り扱いに関する主要なアウトカムについて、AIと人間が評価した場合の類似性を明らかにすることを目的とした。

英国の屠畜場における牛の取り扱いと気絶処理に関する動画クリップ112件を収集した。AIが判定したアウトカムは、気絶処理、電気ムチの使用、転倒、牛舎の過密状態、取り扱いにおける疑わしい事象の有無である。人間の評価者3名もこれらのアウトカムを動画から評定し、ここで作成された4つの異なるデータセットについてジャッカード類似度指数 Jaccard similarity indices (JI) を算出した。

気絶処理、電気ムチの使用、転倒に関しては、人間の評価者とAIの間の類似性は高かった（JI > 0.90）。牛舎の過密状態に関しては、両者の一致度は高かった（JI > 0.80）。取り扱いにおける疑わしい事象の特定に関しては、人間とAIの間で違いが見られたが（JI ≥ 0.50）、追加的な検証を要する事象を特定するうえではAIが優れていた。

AIの実装によって屠畜場における牛の取り扱いを支援することは、動物福祉プログラムを推進するうえで有用な追加ツールとなる可能性がある。

動物の未来-FACTSへ戻る