In a world of rapidly changing technology and creation of more efficient systems, manual labour is slowly becoming a thing of the past, and with this conception of new technology, the application of artificial intelligence (AI) is on the rise.
AI is a branch of computer science that is concerned with building smart machines capable of performing tasks that typically require human intelligence.
The main purpose of artificial intelligence is to enable computers to perform such intellectual tasks as decision-making, problem-solving, perception, and understanding human communication.
What does it mean for agriculture? It means decision-making and reaction time when it comes to important agricultural decisions can be quicker and more precise than ever before, whilst simultaneously giving rise to the extensive use of remotely controlled tractors, greenhouses, or irrigation systems.
AI applications in agriculture help farmers improve accuracy and controlled farming by providing proper guidance to farmers about water management, crop rotation, timely harvesting, types of crops to be grown, optimum planting, pest attacks, and nutrition management.
Benefits of AI include reduction in human error. AI helps reduce the number and severity of errors by adding large-scale data analysis to human judgement in agricultural decisions, and the systems and machines takes risks instead of humans.
Unlike humans, AI only needs a power source and the corresponding software and hardware. From there it is available all day to manage whatever farm activity it has been assigned to manage or participate in. Not only does this cut down production costs that would have been incurred using humans for labour, but it also improves the turnover time, making the production activity easier to complete. With repetitive jobs, AI works with a stored memory of activities which then also makes a performing the same task a walk in the park.
Other benefits of AI are the digital assistance it provides where information is readily available online, and uploading and updating of farming related programmes can be done to expedite decision-making.
There are four types of AI:
- Reactive AI
- Limited memory AI
- Theory of mind AI
- Self-awareness AI
Reactive AI revolves around the rudimentary AI principles. This form of intelligence can only interpret and process information (visual or auditory) presented to it. A reactive machine does not keep a memory, thus cannot depend on past occurrences for judgement-making instantaneously. Such technology can be used for drones to identify and spray chemicals upon detecting the presence of unwanted weeds, insects or pests.
Unlike reactive AI, limited memory can keep information and make forecasts during data collection, evaluating plausible actions or conclusions. Limited memory AI is quite multifaceted and has a wider scope of application compared to reactive machines. It can be used to predict weather patterns based on historical rainfall patterns.
Theory of Mind is based on the psychological foundation of understanding that other living things have thoughts and emotions that affect the behaviour of one self. With regard to AI machines, the technology would then be able to understand how living creatures and non-living machines feel and are able to make choices by self-reflection and willpower, and afterwards use this data to decide independently how to proceed. A future farm can be run by AI as it is able, for example, to analyse labour force moods based on an analysis of their facial expressions and body language to determine their state of health or exhaustion.
In first world countries all this seems realisable, but in most of the developing countries of Africa, such achievements are beyond the imagination and lack of investment.
Whether Africa is ready for artificial intelligence still remains a question as there will need to be a balance in finding a solution for these challenges without threatening the livelihoods, income and employment of the inhabitants.