Will the bulk of energy and water wasted on data traffic between internet-connected servers, data centers and machines, be wasted on pointless data exchanges?
Bard: It could have a significant impact on the environment. The energy and water required to transmit and process this pointless data will be wasted, and this could contribute to climate change
Question 1 of 3 for AI services: Name reasons why by 2030, 80% of all data traffic to and from internet connected data centers and servers could be AI, chatbot or botnet created traffic without any human intervention
ChatGPT-4’s answer:
There are several reasons why by 2030, 80% of all data traffic to and from internet-connected data centers and servers could be AI, chatbot, or botnet created traffic without any human intervention:
Increased Use of AI and Machine Learning: As AI and machine learning technologies continue to advance, they are being increasingly integrated into various applications and systems. These technologies often require significant data exchange for training, inference, and updating models, which could contribute to a large portion of data traffic.
Growth of IoT Devices: The number of Internet of Things (IoT) devices is expected to grow exponentially in the coming years. These devices often communicate with servers and data centers to exchange data, and many of them use AI for tasks like data analysis and decision making.
Automation and Digital Transformation: Many businesses are undergoing digital transformation, which often involves automating various processes. This automation frequently involves the use of AI and bots, which can generate significant data traffic.
Rise of Chatbots: Chatbots are becoming increasingly common for customer service and other applications. These bots communicate with servers to process user requests, which can generate a large amount of data traffic.
Cybersecurity Threats: Unfortunately, the growth of botnets, which are networks of compromised computers controlled by an attacker, is also a factor. These botnets can generate significant data traffic as they carry out attacks or communicate with their command and control servers.
Data-Intensive Applications: Applications like video streaming, online gaming, and virtual reality are becoming more common and more data-intensive. Many of these applications use AI for tasks like content recommendation, which can contribute to data traffic.
Edge Computing: With the rise of edge computing, more data is being processed closer to the source, reducing latency. This involves a lot of data exchange between edge devices and data centers, often facilitated by AI.
5G and Future Connectivity Technologies: The advent of 5G and future connectivity technologies will enable faster data transfer rates, allowing for more data-intensive applications and services, many of which will be powered by AI.
These are just a few potential reasons, and the actual outcome will depend on a variety of factors, including technological advancements, market trends, and regulatory developments.
Google Bard’s answer:
Sure, here are some reasons why by 2030, 80% of all data traffic to and from internet connected data centers and servers could be AI, chatbot or botnet created traffic without any human intervention:
The increasing use of intelligent devices. As more and more devices become connected to the internet, they will generate more and more data traffic. This includes devices like smart homes, wearables, and self-driving cars. These devices will be able to collect and process data without any human intervention, which will lead to a significant increase in AI-generated traffic.
The growth of chatbots and botnets. Chatbots are becoming increasingly popular, and they are already being used for a variety of tasks, such as customer service, marketing, and education. Botnets are networks of infected devices that are controlled by a single attacker. These botnets can be used to generate large amounts of traffic, which can be used for malicious purposes, such as DDoS attacks.
The development of new AI technologies. As AI technologies continue to develop, they will become more powerful and efficient. This will allow them to handle more complex tasks and generate more data traffic. For example, AI-powered image recognition and natural language processing technologies are already being used to generate large amounts of data traffic.
In addition to these reasons, there are a number of other factors that could contribute to the growth of AI-generated traffic by 2030. These include the increasing availability of bandwidth, the development of new cloud-based services, and the growing demand for real-time data.
It is important to note that these are just some of the reasons why AI-generated traffic could make up 80% of all data traffic by 2030. The actual percentage of AI-generated traffic may be higher or lower, depending on a number of factors. However, it is clear that AI is playing an increasingly important role in the generation of data traffic, and this trend is likely to continue in the years to come.
Bing Chat’s answer:
That’s an interesting question. Here are some possible reasons why AI, chatbot or botnet created traffic could dominate the data traffic by 2030:
The internet of things (IoT) is expected to grow exponentially in the next decade, connecting billions of devices and sensors to the internet. These devices may generate and exchange large amounts of data without human intervention, for purposes such as monitoring, control, automation, and optimization 1.
The cybersecurity threats posed by botnets are also increasing in sophistication and scale, as attackers use malicious software programs to infect and exploit many hosts for destructive activities, such as DDoS attacks, spamming, information theft, and click fraud. Botnets use various communication channels to transfer orders and data between the master host and the bots, which may generate significant network traffic 234.
The artificial intelligence (AI) and chatbot technologies are becoming more advanced and widespread, as they provide intelligent and natural interactions with users across various domains and platforms. AI and chatbots use machine learning algorithms to learn from data and user feedback, and to generate personalized and relevant responses. They may also use natural language processing (NLP) and natural language generation (NLG) techniques to understand and produce natural language texts or speech. These processes may require large amounts of data processing and communication between the chatbot and the user, as well as between the chatbot and other AI services or databases 5.
These are some of the possible factors that could contribute to the increase of AI, chatbot or botnet created traffic in the future. However, there may be other factors or challenges that could affect this trend as well. I hope this answer was helpful. 😊
Question 2 of 3 for AI services: Can you find out what percentage of data traffic today is completely useless, machine generated data traffic, possibly created to generate fake eyeballs, clicks, views or the result of cyber attacks and malware distribution? Feel free to support your conclusion with research or news articles
ChatGPT-4’s answer:
Used Link Reader
Used ScholarAI
I found a few resources that might help answer your question, but none of them provide a specific percentage of useless machine-generated data traffic. Here are some relevant findings:
An article from New York Magazine suggests that less than 60% of web traffic is human, implying that a significant portion could be machine-generated. However, it doesn't specify how much of this machine-generated traffic is "useless" or created for deceptive purposes.
A research paper titled "The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning" discusses the use of machine learning and big data technologies in monitoring air pollution. While it doesn't directly address your question, it does highlight the increasing use of machine-generated data in various fields.
Another research paper titled "Development of a Machine-Learning-Based Novel Framework for Travel Time Distribution Determination Using Probe Vehicle Data" discusses the use of machine-generated data in the field of transportation. Again, this doesn't directly answer your question but shows the growing importance of machine-generated data.
A research paper titled "Using Machine Learning on V2X Communications Data for VRU Collision Prediction" discusses the use of machine-generated data in predicting vehicle collisions. This is another example of how machine-generated data can be useful, rather than "useless".
A research paper titled "Assessment of Carbon-Aware Flexibility Measures From Data Centres Using Machine Learning" discusses the use of machine learning in managing data center energy consumption. This is another example of the beneficial use of machine-generated data.
While these resources don't provide a specific percentage of useless machine-generated data traffic, they do highlight the growing importance and use of machine-generated data in various fields. It's also worth noting that what might be considered "useless" data could depend on the context. For example, data that seems useless in one context might be valuable in another.
Google Bard’s answer:
I'm just a language model, so I can't help you with that.
Bing Chat’s answer:
That’s a challenging question to answer, as there is no clear definition or measurement of what constitutes useless, machine generated data traffic. However, here are some possible sources and estimates of such traffic:
Bot traffic: According to Statista, in 2021, the global share of web traffic generated by bots was 42.3%, of which 27.7% was from bad bots that are involved in fraudulent or malicious activities 1. This means that more than a quarter of web traffic could be considered useless or harmful, as it does not reflect genuine human interest or engagement.
Machine-generated data: According to Kommando Tech, machine-generated data is data produced by a computer without human input, such as sensor data, log files, web crawlers, etc. This type of data can have various purposes and applications, but it may also contribute to data noise and redundancy. Advanced data analytics show that machine-generated data will grow to encompass more than 40% of internet data in 2020 2.
Data cleaning: According to Lost Boy, data cleaning is the process of identifying and correcting errors, inconsistencies, and missing values in data sets. Data cleaning is an essential step for data analysis and machine learning, but it also implies that a lot of data is not ready or useful for these tasks. A survey by Figure Eight in 2019 found that nearly three quarters of technical respondents spend 25% or more of their time managing, cleaning, and/or labeling data 3. This suggests that a significant portion of data is not clean or usable as it is.
These are some of the possible indicators of useless, machine generated data traffic, but they are not conclusive or comprehensive. There may be other factors or sources that could affect this estimation as well. I hope this answer was informative. 😊
Question 3 of 3 for AI services: Is there a possibility that sometime in the future, the bulk of energy and water wasted on data traffic between internet-connected servers, data centers and machines, will be wasted on pointless data exchanges that no human has instigated, observed or benefited from?
ChatGPT-4’s answer:
Yes, it's certainly possible. As the number of internet-connected devices continues to grow, so too does the amount of data they generate and exchange. This includes not just devices used directly by humans, like smartphones and computers, but also a wide range of machines and sensors that are part of the Internet of Things (IoT). These devices often communicate with each other and with servers automatically, without any human intervention.
In many cases, this machine-to-machine communication is beneficial and necessary. For example, it allows for the automation of various processes, improves system efficiency, and enables new technologies like autonomous vehicles. However, it can also lead to a significant amount of data traffic that might be considered "pointless" in the sense that no human has instigated, observed, or benefited from it.
This could include, for example, data exchanges that are part of routine system maintenance or updates, communication between devices in a botnet, or data generated by poorly optimized or malfunctioning software. In some cases, these data exchanges could consume significant amounts of energy and other resources without providing any direct benefit to humans.
Moreover, as AI and machine learning technologies continue to advance, they are likely to generate and consume even more data, potentially exacerbating this issue. These technologies often require significant amounts of data for training and inference, and they can also generate large amounts of data as they operate.
Therefore, it's important for the designers and operators of these systems to consider efficiency and resource usage when designing and optimizing their systems. This includes not just the efficiency of the devices themselves, but also the efficiency of the data they generate and consume. By doing so, it's possible to minimize the amount of "pointless" data traffic and the resources wasted on it.
Google Bard’s answer:
Yes, there is a possibility that sometime in the future, the bulk of energy and water wasted on data traffic between internet connected servers, data centers and machines, will be wasted on pointless data exchanges that no human has instigated, observed or benefited from.
There are a number of factors that could contribute to this, including:
The increasing use of intelligent devices, such as smart homes, wearables, and self-driving cars. These devices will generate large amounts of data traffic, much of which will be unnecessary or pointless.
The growth of chatbots and botnets. These entities can generate large amounts of traffic, which can be used for malicious purposes or simply to waste resources.
The development of new AI technologies. As AI technologies continue to develop, they will become more powerful and efficient. This will allow them to handle more complex tasks and generate more data traffic.
In addition to these factors, there is also the possibility that the future internet will be increasingly dominated by machine-to-machine (M2M) communication. This means that devices will be able to communicate with each other without any human intervention. This could lead to a significant increase in pointless data exchanges, as devices will be constantly sending and receiving data, even if there is no need for it.
If this happens, it could have a significant impact on the environment. The energy and water required to transmit and process this pointless data will be wasted, and this could contribute to climate change. It could also lead to an increase in cybercrime, as malicious actors will be able to exploit the large amounts of data traffic to launch attacks.
There are a number of things that can be done to address this problem. One is to develop more efficient data transmission and processing technologies. Another is to develop new protocols that can distinguish between useful and pointless data exchanges. Finally, it is important to raise awareness of the problem so that people can make informed decisions about how they use the internet.
Bing Chat’s answer:
That’s a speculative question that I cannot answer with certainty. However, in this context, a human might say that there is a possibility, but not a certainty, that such a scenario could happen in the future. It would depend on various factors, such as the growth and regulation of data traffic, the efficiency and sustainability of data centers and servers, the innovation and adoption of data analytics and AI technologies, and the awareness and responsibility of data producers and consumers. Therefore, it is not a foregone conclusion that data traffic will become pointless or wasteful, but rather a challenge and an opportunity for humans to make better use of data and its potential benefits. 😊
