{"id":987510400,"date":"2024-07-18T14:21:48","date_gmt":"2024-07-18T14:21:48","guid":{"rendered":"https:\/\/branding-science.com\/?p=987510400"},"modified":"2025-05-01T14:52:01","modified_gmt":"2025-05-01T14:52:01","slug":"separer-le-battage-mediatique-de-la-realite-dans-le-monde-de-lintelligence-artificielle","status":"publish","type":"post","link":"https:\/\/branding-science.com\/fr\/separer-le-battage-mediatique-de-la-realite-dans-le-monde-de-lintelligence-artificielle\/","title":{"rendered":"S\u00c9PARER LE BATTAGE M\u00c9DIATIQUE DE LA R\u00c9ALIT\u00c9 DANS LE MONDE DE L'INTELLIGENCE ARTIFICIELLE"},"content":{"rendered":"

[et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” custom_padding=”||50px||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/07\/AI-terminology-Blog-assets-banner_.png” alt=”Pharma insights” title_text=”AI terminology – Blog assets-banner_” align=”center” force_fullwidth=”on” _builder_version=”4.25.1″ _module_preset=”default” border_radii=”on|20px|20px|20px|20px” box_shadow_style=”preset1″ locked=”off” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”2_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_2_text_color=”#3d86ae” header_2_font_size_tablet=”” header_2_font_size_phone=”28px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

In the world of hype surrounding the term \u2018Artificial intelligence\u2019 (AI), it\u2019s natural to ask how you can actually define what AI is (and isn\u2019t).<\/h2>\n

[\/et_pb_text][et_pb_divider color=”#edb22e” divider_weight=”3px” _builder_version=”4.23.1″ _module_preset=”default” custom_margin=”10px||5px||false|false” locked=”off” global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font=”Roboto|300|||||||” custom_margin=”||||false|false” locked=”off” global_colors_info=”{}”]<\/p>\n

With many tech providers offering genuinely innovative and valuable solutions under the banner of AI, whilst others use that same banner to sell what is essentially technological \u2018snake oil\u2019, it can be challenging to cut through the noise and spot the difference.<\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” background_color=”#d1e3f2″ background_enable_image=”off” background_size=”custom” background_image_width=”57%” background_position=”center_right” max_width=”100%” custom_margin=”|0px||0px|false|false” custom_padding=”|0px||0px|false|false” background_last_edited=”on|tablet” background_enable_image_tablet=”off” border_radii=”off|16px|16px|16px|16px” global_colors_info=”{}”][et_pb_row column_structure=”2_5,3_5″ make_equal=”on” _builder_version=”4.25.1″ _module_preset=”default” width=”90%” max_width=”2560px” border_radii=”on|5px|5px|5px|5px” global_colors_info=”{}”][et_pb_column type=”2_5″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_font_size=”8px” header_2_text_color=”#182a39″ header_2_font_size=”36px” custom_margin=”||0px||false|false” custom_padding=”||5px||false|false” global_colors_info=”{}”]<\/p>\n

The first thing to say is that AI, as a term, is not new.<\/h2>\n

[\/et_pb_text][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font=”Roboto|300|||||||” text_text_color=”#182a39″ custom_margin=”10px||||false|false” locked=”off” global_colors_info=”{}”]<\/p>\n

Arguments still rage about exactly what that term describes, but taking its broadest possible description (i.e. \u2018any algorithm that mimics human-like behaviour\u2019), it\u2019s clear to see that there are examples that fit into this category going back at least 50 years. From the Ghosts who chase Pac-Man (and each have their own unique ways of chasing the player) to the Deep Blue computer that beat Gary Kasparov at chess, from Spotify\u2019s music recommendation algorithms and all the way through to facial recognition for your iPhone and ChatGPT, human-like computer programmes have permeated our lives for a generation or more.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”3_5″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/05\/AI_Scene_.png” title_text=”AI_Scene_” align=”center” _builder_version=”4.25.1″ _module_preset=”default” max_width=”64%” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_row column_structure=”2_5,3_5″ make_equal=”on” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_column type=”2_5″ _builder_version=”4.25.1″ _module_preset=”default” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/05\/Pac-man-ai.png” title_text=”Pac man ai” _builder_version=”4.25.1″ _module_preset=”default” border_radii=”on|16px|16px|16px|16px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”3_5″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” custom_padding=”||0px||false|false” custom_padding_tablet=”40px||||false|false” custom_padding_phone=”40px||||false|false” custom_padding_last_edited=”on|phone” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/05\/Asset-2.png” title_text=”Asset 2″ align=”center” module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” max_width=”20%” max_width_tablet=”20%” max_width_phone=”30%” max_width_last_edited=”on|phone” module_alignment=”left” custom_margin=”0px||0px||false|false” custom_padding=”0px||25px||false|false” custom_css_free_form=”.selector img {|| animation: floating 3s ease-in-out infinite;||}||||@keyframes floating {|| 0% {|| transform: translate(0, 0);|| }|| 50% {|| transform: translate(0, -10px);|| }|| 100% {|| transform: translate(0, 0);|| }||}” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_font_size=”8px” header_2_text_color=”#3d86ae” header_2_font_size=”36px” custom_margin=”||0px||false|false” custom_padding=”||5px||false|false” global_colors_info=”{}”]<\/p>\n

Why is this important?<\/h2>\n

[\/et_pb_text][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font=”|300|||||||” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”]Because although the Ghosts from Pac-Man are cool and, crucially, are technically AI, they\u2019re no longer the cutting edge of technology. But any na\u00efve or insidious marketeer who wants to repackage Pac-Man and sell it for the latest platforms could quite legitimately say that their new version \u2018leverages AI technology to unlock the game\u2019s truepotential\u2019. Sound familiar?<\/p>\n

A more relevant example would be to take one of the algorithms we use to assist in our quantitative analysis, like a clustering algorithm for a segmentation. A clustering algorithm is part of a group of algorithms called machine learning algorithms, which all fit under this broad AI definition. Therefore, you could legitimately market your segmentations as \u2018AI-enhanced\u2019, which, while technically true, could be interpreted as something completely different.
\n[\/et_pb_text][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/05\/Ghosts.svg” title_text=”Ghosts” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” background_color=”#edb22e” background_image=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/07\/Ai-drop-down-section_.png” background_size=”custom” background_image_width=”57%” background_position=”center_right” max_width=”100%” custom_margin=”100px|0px||0px|false|false” custom_padding=”|0px||0px|false|false” background_last_edited=”on|tablet” background_enable_image_tablet=”off” border_radii=”off|16px|16px||” global_colors_info=”{}”][et_pb_row column_structure=”2_5,3_5″ make_equal=”on” _builder_version=”4.25.1″ _module_preset=”default” width=”90%” max_width=”2560px” border_radii=”on|5px|5px|5px|5px” global_colors_info=”{}”][et_pb_column type=”2_5″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_font_size=”8px” header_2_text_color=”#FFFFFF” header_2_font_size=”36px” custom_margin=”||0px||false|false” custom_padding=”||5px||false|false” global_colors_info=”{}”]<\/p>\n

So how can you look past this marketing ploy to separate the digital wheat from the chaff?<\/h2>\n

[\/et_pb_text][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font=”Roboto|300|||||||” text_text_color=”#FFFFFF” custom_margin=”10px||||false|false” locked=”off” global_colors_info=”{}”]At Branding Science, we\u2019ve developed a series of questions to ask when onboarding AI tools \u2013 both those we\u2019ve built ourselves and those from our AI suppliers \u2013 that we\u2019d like to share with you:<\/strong>
\n[\/et_pb_text][\/et_pb_column][et_pb_column type=”3_5″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/07\/Ai-drop-down-section_.png” title_text=”Ai drop down section_” disabled_on=”off|off|on” _builder_version=”4.25.1″ _module_preset=”default” border_radii=”on|12px|12px|12px|12px” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” background_color=”#fbf0d5″ background_enable_image=”off” background_size=”custom” background_image_width=”0%” background_image_height=”0%” background_position=”bottom_left” background_horizontal_offset=”-2%” background_vertical_offset=”24%” max_width=”100%” custom_margin=”|0px|0px|0px|false|false” custom_padding=”|0px|50px|0px|false|false” border_radii=”off|||16px|16px” global_colors_info=”{}”][et_pb_row _builder_version=”4.25.1″ _module_preset=”default” width=”100%” max_width=”2560px” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion toggle_icon=”3||divi||400″ use_icon_font_size=”on” icon_font_size=”32px” _builder_version=”4.25.1″ _module_preset=”default” max_width=”90%” module_alignment=”center” custom_margin=”||||false|false” custom_padding=”||||false|false” border_radii=”on|16px|16px|16px|16px” border_width_all=”0px” global_colors_info=”{}”][et_pb_accordion_item title=”WHERE, AND FOR HOW LONG, IS THE DATA STORED?” open=”on” open_toggle_text_color=”#FFFFFF” icon_color=”#FFFFFF” _builder_version=”4.25.1″ _module_preset=”default” body_font=”|300|||||||” body_text_color=”#FFFFFF” background_color=”#44637b” background_enable_color=”on” global_colors_info=”{}” toggle_text_color=”#FFFFFF” toggle_font_size=”30px”]There are a variety of standards that different businesses adhere to, based on local regulations, non-mandatory data adherence frameworks and internal compliance regulations. Understanding your company\u2019s rules about data storage and ensuring that your AI providers also store data in accordance with these rules is crucial (for example, ensuring that a provider has EU servers to handle personal data created in the EU).
\n[\/et_pb_accordion_item][et_pb_accordion_item title=”WHAT IS THE PROCESS FOR HANDLING ADVERSE EVENTS (AEs)?” open_toggle_text_color=”#FFFFFF” icon_color=”#FFFFFF” _builder_version=”4.25.1″ _module_preset=”default” body_font=”|300|||||||” body_text_color=”#FFFFFF” background_color=”#44637b” background_enable_color=”on” global_colors_info=”{}” toggle_text_color=”#FFFFFF” toggle_font_size=”30px” open=”off”]Adverse event handling is something that we ensure that everyone who interacts with AI is trained in at Branding Science. However, this may not be the case for many AI suppliers, so establishing if your providers have an appropriately robust AE handling process \u2013 and if not, ensuring that anyone who interacts with AI outputs is appropriately trained \u2013 is vital. This includes AEs contained in the training data, as may well be the case for models trained on social media data such as ChatGPT.
\n[\/et_pb_accordion_item][et_pb_accordion_item title=”HOW ARE BIASES MITIGATED IN THE MODEL OUTPUTS?” open_toggle_text_color=”#FFFFFF” icon_color=”#FFFFFF” _builder_version=”4.25.1″ _module_preset=”default” body_font=”|300|||||||” body_text_color=”#FFFFFF” background_color=”#44637b” background_enable_color=”on” global_colors_info=”{}” toggle_text_color=”#FFFFFF” toggle_font_size=”30px” open=”off”]Understanding where there are biases in the outputs of your AI tools is very important, but also extremely challenging. Only those who have had access to the training data set and have done benchmarking on the outputs will be able to identify what biases exist in the model, which is why it\u2019s vital to understand if any of this benchmarking has happened, and, if it has revealed biases, how those are mitigated.
\n[\/et_pb_accordion_item][et_pb_accordion_item title=”HOW IS THE RISK OF HALLUCINATIONS MINIMISED?” open_toggle_text_color=”#FFFFFF” icon_color=”#FFFFFF” _builder_version=”4.25.1″ _module_preset=”default” body_font=”|300|||||||” body_text_color=”#FFFFFF” background_color=”#44637b” background_enable_color=”on” global_colors_info=”{}” toggle_text_color=”#FFFFFF” toggle_font_size=”30px” open=”off”]Hallucinations are a huge problem for many large language models (LLMs) such as ChatGPT, defined as misleading or otherwise made-up\/false responses to a question that the model will report with absolute confidence. It is possible to put guard rails in place, such as getting an LLM to cite its sources, but even these are not completely foolproof, so it\u2019s critical to understand what safeguards are in place.
\n[\/et_pb_accordion_item][et_pb_accordion_item title=”WHAT IS THE TRAINING DATA SET FOR THE MODEL?” open_toggle_text_color=”#FFFFFF” icon_color=”#FFFFFF” _builder_version=”4.25.1″ _module_preset=”default” body_font=”|300|||||||” body_text_color=”#FFFFFF” background_color=”#44637b” background_enable_color=”on” global_colors_info=”{}” toggle_text_color=”#FFFFFF” toggle_font_size=”30px” open=”off”]As the old computer science saying goes: \u201cgarbage in, garbage out\u201d. In other words, any AI tool will only be as good as the data you train it on, so understanding what the training data represents (and therefore what the model\u2019s outputs should represent) is the single most important thing you should try to understand about any AI product you\u2019re working with.
\n[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”||0px||false|false” custom_padding=”||0px||false|false” global_colors_info=”{}”][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”2_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font=”Roboto|300|||||||” custom_margin=”||||false|false” locked=”off” global_colors_info=”{}”]<\/p>\n

The AI frontier is a brave new world and technological advancements in the field are moving far too quickly for regulators to keep up. This means that, in order to prevent yourself from headaches now (from \u2018snake oil\u2019 sellers) and down the line (from future regulatory decisions), you must develop a widespread understanding of AI terminology and robust guidelines for safe and effective use of AI within your business. Anyone who does not act now will find themselves looking back in a few years\u2019 time, wondering where they got left behind.<\/p>\n

[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_2_text_color=”#3d86ae” header_2_font_size=”32px” header_font_size_tablet=”26px” header_font_size_phone=”26px” header_font_size_last_edited=”on|tablet” header_2_font_size_tablet=”30px” header_2_font_size_phone=”28px” header_2_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

Written 100% by humans, with no AI input<\/h2>\n

[\/et_pb_text][et_pb_divider color=”#edb22e” divider_weight=”3px” _builder_version=”4.23.1″ _module_preset=”default” custom_margin=”10px||5px||false|false” locked=”off” global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_row column_structure=”1_3,2_3″ make_equal=”on” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/branding-science.com\/wp-content\/uploads\/2024\/05\/Gabe-article.png” title_text=”Gabe article” align=”center” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_3″ module_class=”vertical-align” _builder_version=”4.25.1″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_font_size=”22px” header_2_text_color=”#3d86ae” header_2_font_size=”32px” text_orientation_tablet=”center” text_orientation_phone=”center” text_orientation_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n

This article was written by:<\/strong><\/h2>\n

[\/et_pb_text][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” header_2_font=”|300|||||||” header_2_font_size=”25px” custom_margin=”||0px||false|false” custom_padding=”||10px||false|false” text_orientation_tablet=”center” text_orientation_phone=”center” text_orientation_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n

Gabe Musker<\/span><\/h2>\n

[\/et_pb_text][et_pb_text _builder_version=”4.25.1″ _module_preset=”default” text_line_height=”1em” header_2_font=”|300|||||||” text_orientation_tablet=”center” text_orientation_phone=”center” text_orientation_last_edited=”on|tablet” global_colors_info=”{}”]<\/p>\n

Data Scientist<\/span><\/strong><\/p>\n

Gabe.Musker@branding-science.com<\/p>\n

[\/et_pb_text][et_pb_divider color=”#edb22e” divider_weight=”3px” _builder_version=”4.25.1″ _module_preset=”default” custom_margin=”10px||5px||false|false” locked=”off” global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

In the world of hype surrounding the term \u2018Artificial intelligence\u2019 (AI), it\u2019s natural to ask how you can actually define what AI is (and isn\u2019t). With many tech providers offering genuinely innovative and valuable solutions under the banner of AI, whilst others use that same banner to sell what is essentially technological \u2018snake oil\u2019, it […]<\/p>\n","protected":false},"author":1,"featured_media":987510570,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"

Here at Branding Science we have been fortunate to assist numerous companies in conducting advisory boards, fostering many insightful discussions with a range of healthcare professionals.<\/p>

However, these conversations aren\u2019t always a breeze! That\u2019s why we\u2019ve distilled some of our key strategies to ease tension and promote fruitful discussions during ad boards.<\/p>

In our latest article, we\u2019ve shared our top seven tips to bear in mind if you want to conduct a successful ad board.<\/p>

To read our thoughts in full, click here<\/a>.<\/p>","_et_gb_content_width":"","footnotes":""},"categories":[18,1],"tags":[],"class_list":["post-987510400","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-uncategorized"],"yoast_head":"\nSeparating hype from reality in the world of AI | Branding Science<\/title>\n<meta name=\"description\" content=\"How can we separate the wheat from the chaff in the world of hype around Artificial Intelligence? 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