{"id":18998,"date":"2019-03-28T10:04:25","date_gmt":"2019-03-28T09:04:25","guid":{"rendered":"https:\/\/dfge.de\/?page_id=18998"},"modified":"2022-03-11T13:50:07","modified_gmt":"2022-03-11T12:50:07","slug":"download-whitepaper-csr-and-artificial-intelligence","status":"publish","type":"page","link":"https:\/\/dfge.de\/en\/download-whitepaper-csr-and-artificial-intelligence\/","title":{"rendered":"Download Whitepaper “CSR and Artificial Intelligence”"},"content":{"rendered":"

[vc_row content_placement=”middle” css=”.vc_custom_1575390546273{padding-top: 55px !important;padding-bottom: 55px !important;}”][vc_column][vc_row_inner equal_height=”yes” content_placement=”middle”][vc_column_inner width=”2\/3″ css=”.vc_custom_1575390506246{margin-top: 30px !important;margin-bottom: 30px !important;}”]

<\/div>

Whitepaper CSR and AI<\/h3><\/div>
<\/p>\n
\n
\n

See the potential!<\/p><\/div>\n<\/div>\n

<\/div><\/div>[vc_column_text css_animation=”fadeInLeft”]The shift towards data-driven CSR management is promoted and accelerated by Artificial Intelligence. Methods to analyze and compare sustainability-related textual data will not only increase efficiency but also scalability. This is relevant, as it is time-consuming, error-prone and rather subjective to process large amounts of text manually, especially since these documents often contain rich and ambiguous natural language. A content analysis of texts about sustainability and CSR-related topics provides valuable insights, for instance regarding upcoming CSR trends. It also enables sectoral benchmarking or quality checks for sustainability reporting.<\/p>\n

The DFGE Whitepaper \u201cAutomatic Analysis of Textual CSR Data<\/span>\u201d introduces methodologies and use cases for an automated analysis of CSR-related textual data.[\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/3″][vc_icon icon_fontawesome=”fas fa-info” color=”black” background_style=”rounded” align=”center”]