Dawood used this approach to simplify his purely technical point of view regarding the size of the impact of artificial intelligence on the music industry, but this analogy may not seem appropriate to the experts in artificial intelligence. Given that artificial intelligence, although it cannot “cook” directly, it can probably do much more difficult than that, given the opportunities it offers in the field of the food industry in general.. so how?
“Artificial intelligence will have a greater impact on the food industry, as it will transform various aspects of the supply chain and production processes, quality and customer experiences, as well as sustainability efforts and some other aspects,” confirms an expert in information technology from the United States, Dr. Ahmed Banafa, in exclusive statements. For the “Sky News Arabia Economy” website.
In points, the professor and academic advisor at San Jose State University, USA, explains the most prominent aspects of the use of artificial intelligence in the food industry, as well as the most prominent challenges and ways to overcome a large part of them. The most prominent uses were represented in seven main aspects, as follows:
- Precision farming
AI enables farmers to improve crop harvesting and reduce resource waste; By analyzing data from sensors, satellites, and drones, machine learning algorithms can help predict weather patterns, detect diseases in plants, and determine the optimal time to harvest. - Food safety and quality control
Artificial intelligence algorithms can be used to monitor and analyze data from sensors, cameras, and other devices to identify potential contaminants, spoilage, or defects in food products; This helps ensure food safety and quality, and reduce disease, in addition to increasing consumer confidence. - Supply chain optimization
AI can improve the efficiency of the food supply chain by improving inventory management and forecasting demand patterns, as well as streamlining logistics. - Personal recommendations and customer experience
AI-powered recommendation systems can analyze customer preferences, dietary restrictions, and purchasing behavior to provide personalized food recommendations; This enhances the customer experience, increases customer loyalty, and drives sales in the food industry. - Food product development
Artificial intelligence can help develop new food products, by analyzing extensive databases of recipes, ingredients and nutritional information, helping to create unique and desirable food offerings. - sustainable agriculture and production
Artificial intelligence technologies also help improve the use of resources and reduce the environmental impact of agriculture and food production, so that AI-powered systems can improve water management, improve energy consumption, and reduce the use of pesticides and fertilizers, which supports the promotion of sustainable practices. - Reducing food waste
Artificial intelligence can play a critical role in reducing food waste at all stages of the supply chain, by analyzing data such as stock levels, order patterns, and expiration dates. Artificial intelligence algorithms can also improve production, distribution, and inventory management. AI-powered systems can predict consumer demand more accurately, reducing the likelihood of unsold products and waste.
With the ability to quickly process and analyze large amounts of data, AI can provide actionable insights to prevent food waste and improve resource use.
Six major challenges
On the other hand, Dr. Ahmed Banafa, in his interview with “Sky News Arabia Economy”, lists some potential defects and challenges, which he believes must be taken into account, including six main factors:
- Lack of human touch
- Limited data quality and bias
- Privacy and data security concerns
- ethical considerations
- lay off jobs
- System failure.. and technical gaps
He explains these elements, first by noting that “AI systems lack human intuition, creativity, and understanding of context,” arguing that in certain aspects of the food industry, such as recipe development or customer service, human touch and personal interactions may be preferred over automated AI systems. .
Also, artificial intelligence algorithms rely heavily on data for training and decision-making. If the input data is of low quality, incomplete or biased, it may lead to inaccurate or biased results; Biased data can perpetuate inequality or discriminatory practices, especially in areas such as dietary recommendations or hiring algorithms.
It also draws attention to privacy concerns, noting that AI systems in the food industry often collect and process vast amounts of personal data, including dietary preferences, health information, and purchasing behaviour.
The nature and method of accessing this data is critical to maintaining consumer confidence and complying with privacy regulations.
In connection with this, he also points out that the use of artificial intelligence raises “ethical concerns” that must be carefully addressed. For example, AI can be used to manipulate or deceive consumer choices through personalized ads or recommendations.
Transparency, explainability, and fairness in AI systems are essential to ensuring ethical use and mitigating potential harm.
Dr. Ahmed Banafa also touches on another challenge, which is the “displacement of jobs”, stressing that automation enabled by artificial intelligence technologies, may lead to layoffs and disruption of the workforce in certain areas of the food industry; It is critical to consider the social and economic impact of AI adoption and ensure appropriate reskilling or re-employment opportunities for affected workers.
With regard to the challenge associated with system failure, the expert specializing in information technology indicates that excessive reliance on artificial intelligence systems can lead to vulnerabilities, as system failures, technical vulnerabilities or cybersecurity breaches can lead to disruption of operations and potential impact. on food safety, supply chain management, or customer experiences.
Robust backup plans and contingency measures are necessary to mitigate these risks.
Addressing defects
In the context, Banafa points out that to address these shortcomings and challenges, it is important to adopt responsible AI practices, ensure transparency, enhance cooperation between humans and AI systems, and regularly evaluate the effects and results of AI applications in the food industry.
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