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With the given amount of spices, we have access to and use on a daily basis one might think, “There is nothing new I can create to change up the taste in my food.” Just based on our knowledge and senses we hit a wall when it comes to creating new flavours. However, this is not the case with the introduction of artificial intelligence (AI) within the spice mixes and flavour field.

McCormick & Company, an already established and long-serving innovator and pioneer within the foods, ingredients, and flavours industry, have partnered up with IBM to launch its first AI-enabled product platform called ONE (IBM, 2019). McCormick is looking to start a flavour revolution by pushing the limits of different spice mixes and innovating large amounts of unique and different flavours (IBM, 2019). McCormick and IBM have worked on this platform that will be using multiple machine learning algorithms that are trained to use data points which will then be used by human product developers to create new ingredients and spice mixes (Handley, 2019). The partnership between the two companies includes McCormick providing their deep data and expertise in science and taste to be paired with the AI capabilities and technology solutions of IBM (Handley, 2019). The platform ONE has already resulted in new unique flavours that will be sold in stores, Tuscan chicken, bourbon pork tenderloin, and New Orleans sausage (Wiggers, 2019).

The implications of AI within the flavour industry is that it will rapidly further innovation to go beyond what it is now capable of (McCormick & Company, 2021). For McCormick and its workforce, AI means that they are able to explore a wider range of new flavour combinations efficiently and quickly to meet the growing market demands (McCormick & Company, 2021). Companies like McCormick can also further pursue different avenues of AI application in the food industry such as McCormick’s current endeavour in the gastronomy field to innovate and create new fusions of flavours based on the science and data that AI collects and analyses (Wiggers, 2019). How far do you think AI will go within the flavours and food industry? Will AI ultimately replace the originality of top chefs by giving them all the answers to the next best flavourful dish?

References:

Handley, L. (2019, February 5). Now A.I. might decide how your food tastes. CNBC. Retrieved September 20, 2022, from https://www.cnbc.com/2019/02/04/mccormick-and-ibm-are-using-ai-to-decide-how-food-is-flavored.html

IBM. (2019, February 4). McCormick & Company and IBM announce collaboration pioneering the use of artificial intelligence in flavor and Food Product Development. IBM Newsroom. Retrieved September 20, 2022, from https://newsroom.ibm.com/2019-02-04-McCormick-Company-and-IBM-Announce-Collaboration-Pioneering-the-Use-of-Artificial-Intelligence-in-Flavor-and-Food-Product-Development

McCormick & Company. (2021, January 12). 5 ways McCormick is reinventing the art and science of flavor. 5 Ways McCormick is Reinventing the Art and Science of Flavor | Flavor Leadership. Retrieved September 20, 2022, from https://www.mccormickcorporation.com/en/news-center/blog/articles/2019/10/23/19/13/5-ways-mccormick-is-reinventing-the-art-and-science-of-flavor

Wiggers, K. (2019, February 4). IBM and McCormick blend new seasonings with ai. VentureBeat. Retrieved September 20, 2022, from https://venturebeat.com/ai/ibm-and-mccormick-stir-new-spice-blends-with-ai/

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“Hello, my name is Molly. I am your virtual medical assistant. How can I help you?” This is the new opening line for patients today and in the future will start hearing first. A patient who wants to know why they have severe headaches has to call their doctor, schedule an appointment, go to the doctor, wait for a long time, meet the doctor, to just have them say the 3 famous words, “Take a paracetamol.” With the emergence of artificial intelligence (AI) powered chatbots, the patient’s journey will be cut in half from the first step (Sennaar, 2019).

Natural language processing (NLP) is the underlying technology for chatbots. This technology falls under AI, having the aim of analysing texts through computerized means and gathering knowledge on how humans understand and use language (Joseph et al., 2016). NLP technology application is evident in many industries due to the technology’s ability to recognize human speech, understand and process natural language, generate text that can be read and interpreted by humans, and measure the sentiment behind certain speech and text (Eggers et al., 2018). Within the healthcare industry it is become more important due to its aforementioned abilities to search, analyse, and interpret large amounts of patient datasets (Foresee Medical, n.d.). Current areas of impact for NLP within the healthcare industry are in remote prevention and care, diagnostics support, treatment pathways support, drug discovery and development, operations, marketing and sales, and other support functions (Aboshiha et al., 2021).

Chatbots within healthcare aim to handle simple tasks of medical professionals which helps save them time to focus on their actual job more and eliminate unnecessary work on their behalf (Teo, 2022). Chatbots ask simple questions and based on the patient’s answers, analyse it and provide solutions if that’s to provide the patient with health-related information, set up appointments, give appointment reminders, and provide health condition information when the patient explains their symptoms (Curtis, 2021). The introduction of chatbots to serve as a supporting technology within the healthcare value chain has provided a list of benefits such as enhanced patient engagement, symptom assessment before in-person appointments, doctor and patient consultation management, reduced waiting times, cost reduction, scalability, and timely medical advice (Mousumi, 2022; Teo, 2022). The video below depicts how this could like, illustrating Sensely’s Virtual Medical Assistant in action (ExpectLabs, 2015).

The future of chatbots is bright as it is predicted that AI and NLP technology will constantly be improving and developing to further enhance the patient journey and for the healthcare provider (Eggers et al., 2018). However, with such technology one should be aware of its challenges such as trust issues among patients due to privacy and doctors leaving it all up to “robots”, cybercrimes, and the question, “Who is accountable if something goes wrong?” (Thomas, 2022).

References

Aboshiha, A., Gallagher, R., & Gargan, L. (2021, December 15). Chasing value as AI transforms health care. BCG Global. Retrieved September 19, 2022, from https://www.bcg.com/publications/2019/chasing-value-as-ai-transforms-health-care

Curtis, B. (2021, November 22). Chatbots in Healthcare: 5 best solutions and use cases. YourTechDiet. Retrieved September 19, 2022, from https://yourtechdiet.com/blogs/healthcare-chatbots-2/

Eggers, W. D., Malik, N., & Gracie, M. (2018). (rep.). Using AI to unleash the power of unstructured government data (pp. 1–20). Deloitte Insights.

ExpectLabs. (2015, June 18). Sense.ly virtual nurse, powered by Mindmeld. YouTube. Retrieved September 19, 2022, from https://www.youtube.com/watch?v=gUfRc_aIntA&t=17s

Foresee Medical. (n.d.). Natural language processing in healthcare medical records. ForeSee Medical. Retrieved September 19, 2022, from https://www.foreseemed.com/natural-language-processing-in-healthcare

Joseph, S. R., Hlomani, H., Letsholo, K., Kaniwa, F., & Sedimo, K. (2016). Natural Language Processing: A Review. International Journal of Research in Engineering and Applied Sciences, 6(3), 207–210. https://doi.org/https://www.researchgate.net/profile/Sethunya-Joseph/publication/309210149_Natural_Language_Processing_A_Review/links/5805ea1f08ae03256b75d965/Natural-Language-Processing-A-Review.pdf

Mousumi. (2022, June 8). Top 5 healthcare chatbot uses cases. Kommunicate Blog. Retrieved September 19, 2022, from https://www.kommunicate.io/blog/top-5-use-cases-of-chatbots-in-healthcare/

Sennaar, K. (2019, December 13). Chatbots for healthcare – comparing 5 current applications. Emerj Artificial Intelligence Research. Retrieved September 19, 2022, from https://emerj.com/ai-application-comparisons/chatbots-for-healthcare-comparison/

Teo, P. (2022, February 21). Healthcare Chatbots: Use cases, examples and benefits. KeyReply. Retrieved September 19, 2022, from https://keyreply.com/blog/healthcare-chatbots/

Thomas, L. (2022, May 4). The Pros and cons of Healthcare Chatbots. Medical News . Retrieved September 19, 2022, from https://www.news-medical.net/health/The-Pros-and-Cons-of-Healthcare-Chatbots.aspx#:~:text=Moreover%2C%20as%20patients%20grow%20to,self%2Ddiagnose%20once%20too%20often.