Sentient Robot: The Dawn of AI Consciousness?
There has been a lot of discussion regarding Artificial Intelligence (AI) sentient robots and the idea that they could ultimately rule the human population. An AI sentient robot is a machine that can move and behave like a human being. As such, it is capable of having feelings, emotions, consciousness of itself, an identity, and an understanding of its place in the world. If such robots were to exist, many believe that they could surpass human cognition, with their phenomenal speed of processing, extensive knowledge base and rapid decision making.
The AI Dilemma: Can A Sentient Robot Experience Feelings?
Philosophers and psychologists have debated the distinction between emotions and feelings for centuries, and it remains unclear. Consider a situation where you are walking home alone late at night, down a dimly lit street. You hear a sudden loud noise behind you, which causes you to jump and makes your heart race. This unexpected loud noise triggers a physiological fear response. However, your feeling will depend on how you interpret that noise. If you think it might be a threat (such as an attacker), you will more than likely feel scared or anxious and may want to hide or run away. However, if you think it’s something harmless (a car backfiring, a falling branch), you might feel startled and quickly dismiss it. On the other hand, curiosity might get the better of you, and you might want to investigate the cause of the noise.
So how can a sentient robot be capable of experiencing and exhibiting similar feelings and emotions?
Essentially, AI consists of one or more models (algorithms or mathematical operations) that programmers implement using programming languages to mimic the basic structure of human neural networks. These networks consist of layers of interconnected nodes that that learn to identify and represent complex patterns. These patterns are derived by training the model on massive datasets, adjusting parameters to minimise the difference between predicted and actual outcomes. The better the model, the closer the prediction to the actual result and the outcome becomes closer to reality.
As humans deepen their understanding of themselves, both mentally and physically, they will try to replicate this knowledge in machines. They may also seek to incorporate features observed in other animals, such as the ability to fly or swim. Philosophers and psychologists may be crucial in breaking down feelings and emotions into discrete components. AI technologists can use these components to develop models and memories that closely resemble, if not perfectly replicate, human reality. This endeavour is already underway, known as affective computing, which involves enabling machines to recognise, interpret, process, and simulate human emotions.
Many companies are already employing these technologies today, e.g.
- Affectiva: Provides software that detects emotions like happiness, sadness, anger, and surprise in facial expressions and speech intonations. While not a sentient robot itself, this technology mimics aspects of sentient robot behaviour by allowing businesses across various sectors, including market research, advertising, the automotive industry, and healthcare, to gauge consumer reactions to videos, ads, and TV shows.
- Open AI Chat GPT: Chatbots used in customer services can identify customer frustration or positive sentiment in text, allowing for more appropriate and helpful responses. For example, Salesforce uses GPT-4 for customer support analysis.
- Google: While not a sentient robot itself, this technology utilises natural language processing and computer vision to understand and interpret human emotions from text, images, and videos, mimicking aspects of sentient robot behaviour. For example, Google Assistant might offer words of comfort when detecting sadness in a user’s query, adjusting its tone to be more empathetic based on the user’s emotional state, or provide relevant support information based on perceived emotions during a conversation.
- IBM: IBM Watson can analyse human emotions through speech and text, mimicking aspects of sentient robot behaviour. These services find applications in various domains, such as customer service, healthcare, and marketing. For example, Watson assists oncologists in making more informed treatment decisions by analysing patient data and treatment responses.
- Amazon: AWS provides access to a suite of AI and machine learning services, including emotion detection and sentiment analysis. These services enable businesses to build applications that understand and respond to human emotions. In June 2024, reports revealed that Amazon used AI cameras to detect the emotions of UK train users with the aim of enhancing passenger safety and improving customer service.
Affective Computing: The Sentient Robot ~ Promises and Perils
The advancement of affective computing presents significant potential, but also raises important ethical concerns, for example:
1.The Evolving Threat: Privacy Violations in the Age of Sentient Robots:
(i) Constant emotion monitoring is uncomfortable, eroding our sense of personal freedom and privacy.
(ii) The storage of emotional data may result in misuse or exploitation with severe consequences.
2. Manipulation and Exploitation of Sentient Robots:
(i) Companies and governments may utilise affective computing to influence individual emotional states through the deployment of targeted advertisements, propaganda techniques, or even mechanisms designed to exert social control.
(ii) Systems designed to exploit vulnerabilities, such as triggering anxiety or fear, which could result in devastating consequences for individuals and society.
3. The Mirror of Prejudice: Bias and Discrimination in Sentient Robots:
(i) Affective computing algorithms trained on biased datasets may perpetuate and even exacerbate existing societal prejudices.
(ii) The potential exists for biased or discriminatory outcomes in areas including hiring processes, loan application evaluations, and even the judicial system.
4. Unpredictable and Unexplainable: The Dangers of Lack of Transparency in Sentient Robots:
(i) Many affective computing systems operate as “black boxes,” making it difficult to understand how they arrive at their conclusions.
(ii) This lack of transparency can make it hard to identify and address biases or errors in the system.
5. The Dangers of Artificial Intimacy: Emotional Manipulation in Social Interactions with Sentient Robots:
(i) The use of affective computing to make a social connection for insincere reasons could result in a harmful relationship both mentally and physically.
(ii) If people use AI to mask their true emotions in order to avoid negative social interactions, it could result in a deceitful relationship.
6.Anxiety, Depression, and the Rise of the Sentient Robots:
(i) Constantly monitoring emotions may negatively impact mental health by increasing anxiety and stress, and creating a feeling of constant judgment.
(ii) Targeted advertising that exploits an individual’s anxieties or insecurities, based on their emotional data could exacerbate feelings of inadequacy and low self-esteem, which could have negative impacts on their mental and emotional well-being.
As with all technology, the actual risks will depend on how we develop, deploy, and regulate affective computing technologies.
