  {"id":14720,"date":"2021-04-20T21:13:10","date_gmt":"2021-04-21T01:13:10","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/wordsmith-ai-powered-narratives-in-human-friendly-prose\/"},"modified":"2021-04-20T21:13:10","modified_gmt":"2021-04-21T01:13:10","slug":"wordsmith-ai-powered-narratives-in-human-friendly-prose","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/wordsmith-ai-powered-narratives-in-human-friendly-prose\/","title":{"rendered":"Wordsmith: AI-powered Narratives in Human-Friendly Prose"},"content":{"rendered":"<p>The next AP article you read on Apple\u2019s second quarter earnings might not be written by humans. Not by aliens either, but by a powerful natural language generation (NLG) platform called Wordsmith. Developed by business intelligence company Automated Insights, Wordsmith takes in structured data, uses AI to interpret it, and spits out human-friendly prose narratives such as summaries, headlines, and articles that explain said data. Wordsmith is sold in a SaaS format, with background computations and analysis done in the cloud.<\/p>\n<p>&nbsp;<\/p>\n<p>While the platform won\u2019t be churning out a Pulitzer-winning article anytime soon, it does save writers considerable time by automatically fleshing out the simpler, \u201clow hanging fruit\u201d insights, and could even come up with a few unique insights that the user didn\u2019t consider. Going back to the Apple example, a business journalist might input the company\u2019s quarterly financials into Wordsmith and the platform will return a few blurbs on how revenue increased x% YoY, commentary on EBITDA margin evolution, and insights on the volume of iPads sold.<\/p>\n<p>&nbsp;<\/p>\n<p><a title=\"\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-14719\" src=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog.jpg\" alt=\"\" width=\"810\" height=\"496\" srcset=\"https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog.jpg 810w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog-300x184.jpg 300w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog-768x470.jpg 768w, https:\/\/d3.harvard.edu\/platform-digit\/wp-content\/uploads\/sites\/2\/2021\/04\/api-pl-blog-600x367.jpg 600w\" sizes=\"auto, (max-width: 810px) 100vw, 810px\" \/><\/a><\/p>\n<p>The possibilities of this platform seem endless, going beyond journalism and into basically any situation (including personal and professional settings) that requires making sense of data. Examples include writing internal company memos, creating end of quarter presentations, or gaining insights from your bank account activity. According to a report from the International Data Corporation, global data generation will likely increase to about 163 zettabytes (sextillion bytes) by 2025, which means that we will need all the help we can get in making sense of it all.<\/p>\n<p>&nbsp;<\/p>\n<p>While Wordsmith is making substantial progress in helping users interpret vast amounts of data, it still has a long way to go in terms of ease of use and how \u201cnatural\u201d its NLG output actually sounds. Wordsmith users on software review website G2 note that, while the platform has saved them hours in processing and interpreting data, its dashboards can be overwhelming and confusing at times. Initial set up time is also a common pain point, described as time consuming and highly technical. There is also room for improvement on the NLG output, which sometimes sounds too \u201crobotic\u201d and requires that users go back and give it the human touch.<\/p>\n<p>&nbsp;<\/p>\n<p>User experience issues such as ease of use are probably a straight-forward fix for Automated Insights, which should be able to iron them out as it collects more user feedback. As for the quality of NLG output, improvement will depend on how powerful its underlying AI technology is, which determines the platform\u2019s capacity to learn and refine after each iteration. Beyond these two fronts, Automated Insights can further its mission to help make sense of the world\u2019s data by developing integrations with other popular business intelligence solutions. Its partner network already includes important players such as Tableau, and by further expanding this network the company will ensure its relevance in the space and facilitate adoption by organizations and individual users.<\/p>\n<p>&nbsp;<\/p>\n<p>Looking forward, one could reasonably expect that AI capabilities such as Wordsmith\u2019s will become even more powerful and sophisticated, enabling full writeups with vivid, human-like commentary at the click of a button. Automated Insights should tread carefully as its technology progresses \u2013 in an ideal future, data interpretation will remain clear, objective, and impartial. However, this is an unlikely scenario, seeing as how we\u2019re already highly adept at bending information to suit our needs (without the help of any sophisticated technology). The ability to generate toxic, manipulative, or dangerous narratives in an instant could open (even more) the floodgates to misinformation, so Automated Insights should place extra care in ensuring that its AI technology remains fully impartial. Leave political commentary to humans, and maybe a robot might snatch a Pulitzer after all.<\/p>\n<p>&nbsp;<\/p>\n<blockquote class=\"wp-embedded-content\" data-secret=\"0jSqGTK7Y4\"><p><a href=\"https:\/\/automatedinsights.com\/\">Automated Insights: Natural Language Generation<\/a><\/p><\/blockquote>\n<p><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Automated Insights: Natural Language Generation&#8221; &#8212; Automated Insights\" src=\"https:\/\/automatedinsights.com\/embed\/#?secret=0jSqGTK7Y4\" data-secret=\"0jSqGTK7Y4\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n<p>https:\/\/sourceforge.net\/articles\/qa-automated-insights-business-intelligence-analytics-natural-language-generation-wordsmith\/<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wordsmith is using Natural Language Generation (NLG) to create written analysis in a heartbeat.<\/p>\n","protected":false},"author":18524,"featured_media":14721,"comment_status":"open","ping_status":"closed","template":"","categories":[2639,1175,2542],"class_list":["post-14720","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-artifical-intelligence","category-journalism","category-natural-language-processing","hck-taxonomy-organization-absa-bank-limited"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/machine-learning\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - 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