Step-by-step explanation:
Turing's criteria for computer software being "intelligent" is known as the Turing test, which involves a human evaluator having a conversation with both a human and a machine (hidden from the evaluator) and then attempting to distinguish which is which based on their responses alone.
While the Turing test was an important contribution to the development of artificial intelligence and remains a widely used benchmark for evaluating conversational agents, it has several limitations. One of the main criticisms of the Turing test is that it only measures a narrow aspect of intelligence, namely the ability to mimic human conversation, and it ignores other important aspects of intelligence, such as creativity, problem-solving, and learning. Additionally, some argue that passing the Turing test does not necessarily imply true intelligence but only the ability to imitate it.
In my opinion, a more comprehensive criteria for computer software to be considered "intelligent" should include the following:
1. Learning and Adaptation: The software should be able to learn from its environment, adapt to new situations, and improve its performance over time.
2. Creativity: The software should be able to generate novel and useful ideas or solutions, and not just rely on pre-programmed rules or data.
3. Problem-solving: The software should be able to solve complex problems, including those that require reasoning, decision-making, and planning.
4. Contextual Understanding: The software should be able to understand the context in which it operates, including the user's intentions, preferences, and emotions, and respond appropriately.
5. Autonomy: The software should be able to operate without human intervention, make decisions on its own, and interact with the environment in a meaningful way.
6. Ethical and Social Responsibility: The software should adhere to ethical and social norms, and be transparent and accountable for its actions and decisions.
Overall, these criteria provide a more holistic approach to evaluating intelligence in software, and acknowledge the complexity and diversity of human intelligence.