senso-concept-Mcs (Algosoc)

McsHitp-creation:: {2020-10-17}

overview of Algosoc

· autonomous-society is a-society algorithmically centralized, AND decentralized in decision-making.
· decentralized-autonomous-society is a-decentralized-society with governance-algorithms.
· decentralized-autonomous-society is a-decentralized-society that uses information-machines in its governance.

* McsEngl.McsStn000019.last.html//dirStn//dirMcs!⇒Algosoc,
* McsEngl.dirMcs/dirStn/McsStn000019.last.html!⇒Algosoc,
* McsEngl.Algosoc!=McsStn000019, {2024-04-09}
* McsEngl.Algosoc!=open-algorithmic-society,
* McsEngl.Autosoc!⇒Algosoc,
* McsEngl.admin-by-algorithm--society!⇒Algosoc,
* McsEngl.algorithmic-society!⇒Algosoc,
* McsEngl.autonomous-society!⇒Algosoc,
* McsEngl.socAlgo!⇒Algosoc, {2024-05-07}
* McsEngl.socAuto!⇒Algosoc, {2023-12-18}, {2023-07-14},
* McsEngl.socOto!⇒Algosoc, {2023-12-18},

* DAS-(Decentralized-Autonomous-Society)!⇒Algosoc, {2022-07-31},
* Das-(Decentralized-Autonomous-Society)!⇒Algosoc,
* DeSociety!⇒Algosoc, {2021-11-06},
* decentralized-autonomous-society!⇒Algosoc,
* socDa!⇒Algosoc,
* socDeAuto!⇒Algosoc,
* socDea!⇒Algosoc, {2023-12-12},
* socDecAut!⇒Algosoc,
* socDca!⇒Algosoc, {2021-04-12},
* socDecentralized.autonomous!⇒Algosoc,
* society.006-centralizedNo.autonomous!⇒Algosoc,
* society.centralizedNo.autonomous!⇒Algosoc,
* society.decentralized.autonomous!⇒Algosoc,
====== langoGreek:
* McsElln.αυτόνομη-κοινωνία!=Algosoc,
* αυτόνομη, όχι αυτόματη,

· a-prerequisite for a-Algosoc is the-machines to understand natural-language-laws.

">automated vs autonomous:
The terms "automated" and "autonomous" are often used in technology and engineering contexts, but they have distinct meanings:
1. **Automated**: Automation refers to the use of various control systems for operating equipment such as machinery, processes in factories, boilers, and heat treating ovens, switching in telephone networks, steering and stabilization of ships, aircraft and other applications with minimal or reduced human intervention. Some processes have been completely automated. The key characteristic of automation is that it follows pre-programmed instructions to execute a task or a series of tasks.
2. **Autonomous**: Autonomy implies a higher level of sophistication. An autonomous system can make decisions and perform tasks independently, without human intervention. It is not just following a set of predefined rules or instructions, but it has the ability to adapt, learn, and make decisions based on its environment and circumstances. Autonomous systems are often associated with artificial intelligence and machine learning, enabling them to react and adapt to changing situations.
In summary, while automated systems operate according to a fixed set of instructions, autonomous systems have the capability to make decisions and adapt based on their environment and inputs. This distinction is particularly relevant in fields like robotics, vehicle systems (like self-driving cars), and AI-driven processes."
[{2023-12-27 retrieved}]

prerequisite of Algosoc

* visible-hand: a-info-network that will-connect production and consumption with real and real-time information.
* algorithmic-administration.
* classless-society.
* autonomous-technology.
* law-system understandable by machines.
* a-consistent international-language for humans and machines (lagSngo?), which requires machines to understand our stored knowledge.
* autonomous-science.
* transparency.

* McsEngl.Algosoc'att004-prerequisite,
* McsEngl.gvcAuto'prerequisite,
* McsEngl.prerequisite-of-Algosoc,

human-system of Algosoc

* a-classless society,

* McsEngl.Algosoc'att002-human-system,
* McsEngl.Algosoc'human-system,

algorithmic-economy of Algosoc

· a-prerequisite of Algosoc.
· no employers and employees, only workers.

· the-autonomous-economy has an-information-network that connects all the-production and consumption organizations to have real and real-time information about the-economy.

* McsEngl.Algoecon!=algorithmic-economy, {2024-07-21}
* McsEngl.Algosoc'att001-economy!⇒Algoecon,
* McsEngl.Algosoc'economy!⇒Algoecon,
* McsEngl.Algosoc'node-of-satisfiers!⇒Algoecon,
* McsEngl.Autoecon!⇒Algoecon,
* McsEngl.Socecon.015-autonomous!⇒Algoecon,
* McsEngl.admin-by-algorithm--economy!⇒Algoecon,
* McsEngl.autonomous-economy!⇒Algoecon,
* McsEngl.econAuto!⇒Algoecon, {2023-12-27},
* Deaecon!⇒economy-of-Algosoc,

visible-hand of Algoecon

· the-autonomous-economy has an-information-network that connects all the-production and consumption organizations to have real and real-time information about the-economy.
· the-production is on-demand with minimun waste of resources.
· "visible-hand" is NOT the-managerial revolution, NOR the-government intervention in the-economy, but the-information-network which will-replace the-market.

* McsEngl.Algoecon'att008-visible-hand,
* McsEngl.Algoecon'visible-hand,
* McsEngl.the-visible-hand-of-Algoecon,
* McsEngl.visible-hand-of-Algoecon,

producing-system of Algoecon


* McsEngl.Algoecon'att001-production-system,

autonomous-company of Algoecon


* McsEngl.Autocompany!=autonomous-company,
* McsEngl.Algoecon'att007-company!⇒Autocompany,
* McsEngl.Algoecon'company!⇒Autocompany,
* McsEngl.admin-by-algorithm-company!⇒Autocompany,
* McsEngl.autonomous-company!⇒Autocompany,
* McsEngl.ogznProduction.autonomous!⇒Autocompany,

autonomous-worker (link) of Algoecon

consuming-system of Algoecon


* McsEngl.Algoecon'att002-consuming-system,

autonomous-household of Algoecon


* McsEngl.Algoecon'att006-household!⇒Autohousehold,
* McsEngl.Algoecon'household!⇒Autohousehold,
* McsEngl.Autohousehold!=autonomous-household,
* McsEngl.admin-by-algorithm--household!⇒Autohousehold,
* McsEngl.autonomous-household!⇒Autohousehold,
* McsEngl.ogznConsumption.autonomous!⇒Autohousehold,

public-sector of Algoecon


* McsEngl.Algoecon'att003-public-sector,

private-sector of Algoecon


* McsEngl.Algoecon'att004-private-sector,

financial-system of Algoecon


* McsEngl.Algoecon'att005-financial-system,

autonomous-currency (link) of Algoecon

algorithmic-administration of Algosoc

× generic: admnAlgo,
· a-prerequisite of Algosoc.

"Government by algorithm (also known as Algorithmic regulation, Regulation by algorithms, Algorithmic governance, Algocratic governance, Algorithmic legal order or Algocracy) is an alternative form of government or social ordering, where the usage of computer algorithms, especially of artificial intelligence and blockchain, is applied to regulations, law enforcement, and generally any aspect of everyday life such as transportation or land registration.[1][2][3][4][5][6][7] Alternatively, algorithmic regulation is defined as setting the standard, monitoring and modification of behaviour by means of computational algorithms — automation of judiciary is in its scope.[8]
Government by algorithm raises new challenges that are not captured in the e-Government literature and the practice of public administration.[9] Some sources equate cyberocracy, which is a hypothetical form of government that rules by the effective use of information,[10][11][12] with algorithmic governance, although algorithms are not the only means of processing information.[13][14] Nello Cristianini and Teresa Scantamburlo argued that the combination of a human society and an algorithmic regulation forms a social machine.[15]"

* McsEngl.Algoadmn!=algorithmic-administrattion, {2024-07-19}
* McsEngl.Autoadmn!⇒Algoadmn, {2024-01-18},
* McsEngl.Autogvc!⇒Algoadmn, {2023-12-28},
* McsEngl.Algosoc'att003-governance!⇒Algoadmn,
* McsEngl.Algosoc'governance!⇒Algoadmn,
* McsEngl.Socadmn.004=rule-by-algo!⇒Algoadmn,
* McsEngl.Socadmn.rule-by-algo!⇒Algoadmn,
* McsEngl.SocadmnDigi.autonomous!⇒Algoadmn,
* McsEngl.admnAlgo.society!⇒Algoadmn,
* McsEngl.admnAutonomous!⇒Algoadmn,
* McsEngl.algocracy!⇒Algoadmn,
* McsEngl.algocratic-governance!⇒Algoadmn,
* McsEngl.algorithm-governance!⇒Algoadmn,
* McsEngl.algorithmic-governance!⇒Algoadmn,
* McsEngl.algorithmic-government!⇒Algoadmn,
* McsEngl.algorithmic-legal-order!⇒Algoadmn,
* McsEngl.algorithmic-regulation!⇒Algoadmn,
* McsEngl.autonomous-SocadmnDigi!⇒Algoadmn,
* McsEngl.autonomous-administration.society!⇒Algoadmn,
* McsEngl.autonomous-governance!⇒Algoadmn,
* McsEngl.governance-by-algorithm!⇒Algoadmn,
* McsEngl.government-by-algorithm!⇒Algoadmn,
* McsEngl.gvcAuto!⇒Algoadmn,
* McsEngl.gvcHmn.001-autonomous!⇒Algoadmn,
* McsEngl.gvcHmn.autonomous!⇒Algoadmn,
* McsEngl.regulation-by-algorithms!⇒Algoadmn,
* McsEngl.rule-by-algo-of-society!⇒Algoadmn,
====== langoGreek:
* McsElln.αλγοριθμική-διακυβέρνηση!η!=Algoadmn,
* McsElln.αλγοριθμική-διοίκηση!η!=Algoadmn,

autonomous-law (link) of Algoadmn

relation-to-AI of Algoadmn

"could AI govern societies?
Whether AI could govern societies is a complex question with no easy answer. On the one hand, AI has the potential to be a powerful tool for good. It can help us to make better decisions, solve complex problems, and improve the efficiency of government services.

For example, AI could be used to:
* Identify and target resources to areas of greatest need
* Automate repetitive tasks, freeing up human workers to focus on more creative and strategic work
* Detect and prevent fraud and corruption
* Improve the delivery of public services, such as healthcare and education
* Make government more transparent and accountable

On the other hand, there are also some potential risks associated with AI governance. For example, if AI is not used responsibly, it could lead to:
* Discrimination and bias
* Loss of privacy and civil liberties
* Concentration of power in the hands of a few
* Unintended consequences

It is important to note that AI is still in its early stages of development. While AI systems have made impressive progress in recent years, they are still not capable of making complex decisions or governing societies without human oversight.

Ultimately, whether or not AI could govern societies is a question of value and ethics. It is up to us to decide how we want to use AI and how much control we want to give it.

Here are some of the key challenges that need to be addressed before AI could be used to govern societies:
* **Bias:** AI systems are trained on data, and if that data is biased, the AI system will be biased as well. It is important to ensure that AI systems are trained on fair and unbiased data.
* **Privacy:** AI systems collect and process a lot of data, including personal data. It is important to ensure that this data is collected and used in a responsible way, and that people's privacy is protected.
* **Accountability:** It is important to ensure that AI systems are accountable to humans. This means that we need to be able to understand how AI systems make decisions and to hold them accountable for the consequences of their decisions.

Despite the challenges, there is a growing interest in the potential of AI to improve governance. A number of governments and organizations are exploring ways to use AI to make better decisions, improve the delivery of public services, and make government more transparent and accountable.

It is still too early to say whether or not AI will ever be able to fully govern societies. However, it is clear that AI has the potential to play a significant role in shaping the future of governance."
[{2023-10-14 retrieved}]

"could AI govern society?
The idea of AI governing society is a complex and controversial one. AI systems can play a role in assisting with governance, decision-making, and policy implementation, but there are significant ethical, technical, and practical challenges that need to be addressed before AI could play a central role in governing society. Here are some key considerations:

1. Ethics and Values: AI systems are programmed and trained by humans, and they can reflect the biases and values of their creators. Ensuring that AI governance is aligned with the values and ethical principles of a diverse society is a significant challenge.

2. Accountability and Transparency: Transparency and accountability are critical in governance. It's important to know how decisions are made and to be able to hold decision-makers accountable. AI systems can be complex and opaque, making it difficult to understand their decision-making processes.

3. Decision-Making and Bias: AI systems can inadvertently perpetuate and even exacerbate existing biases in society. Ensuring that AI systems make fair and unbiased decisions is a challenge that must be addressed to avoid discrimination and inequality.

4. Unintended Consequences: AI systems can have unintended consequences, and the implications of their decisions can be far-reaching. Ensuring that AI governance takes these consequences into account is crucial.

5. Technological Limitations: AI systems have limitations, and they are not capable of addressing all the complexities of governance. They lack common-sense reasoning, understanding of context, and the ability to deal with unforeseen events effectively.

6. Human Judgment and Accountability: Ultimately, many decisions in governance involve complex moral, ethical, and contextual considerations that require human judgment and accountability. AI should assist and augment human decision-making rather than replace it entirely.

7. Public Trust and Consent: Effective governance relies on the trust and consent of the governed. Introducing AI into governance without public understanding and support could erode trust in the system.

In summary, while AI can play a role in assisting with governance and decision-making, it is unlikely to fully govern society in the foreseeable future. The use of AI in governance must be carefully considered, and it should complement human decision-making, with a focus on ethical, transparent, and accountable use. The development of AI governance systems should involve a multi-disciplinary approach that includes experts in ethics, law, technology, and social sciences to address these challenges and ensure responsible and effective AI use in governance."
[{2023-10-14 retrieved}]

* McsEngl.Algoadmn'relation-to-AI,
* McsEngl.techAi'relation-to-gvcAuto,

info-resource of Algoadmn

* {2023-10},
* {2021-01-25},
* {2021-07-11} Why Real Citizens Would Turn to Artificial Leaders, Nicolas Spatola, Karl F. Macdorman,,

* McsEngl.Algoadmn'Infrsc,

algorithmic-technology of Algosoc

· a-prerequisite of Algosoc.

* AI,
* robotics,
* IoT,
* autonomous-network,
* quantum-computing,

">autonomous technology overview:
**Autonomous technology** (also known as **autonomous systems** or **autonomy**) refers to a field of engineering focused on creating systems that can operate independently without human intervention. These systems typically rely on artificial intelligence (AI), machine learning, and other advanced technologies to perceive their environment, make decisions, and take actions.

**Key characteristics of autonomous technology:**
* **Self-directed:** Autonomous systems can set their own goals and objectives, without the need for external control.
* **Adaptive:** They can adjust their behavior to changing conditions and unforeseen circumstances.
* **Learning:** They can continuously improve their performance through experience and feedback.

**Applications of autonomous technology:**
Autonomous technology has the potential to revolutionize a wide range of industries and applications, including:
* **Transportation:** Self-driving cars, trucks, and drones are becoming increasingly sophisticated and could revolutionize transportation.
* **Agriculture:** Autonomous robots can perform tasks like harvesting, weeding, and planting, improving efficiency and reducing labor costs.
* **Manufacturing:** Automated robots can perform repetitive tasks with precision and consistency, enhancing productivity and safety.
* **Healthcare:** Surgical robots can perform minimally invasive procedures with greater accuracy and precision.
* **Home automation:** Smart devices can control appliances, lighting, and security systems, making homes more convenient and efficient.

**Challenges and ethical considerations:**
While autonomous technology offers immense potential, it also raises significant challenges and ethical considerations:
* **Safety:** Ensuring the safety of autonomous systems is paramount, as any accidents could have severe consequences.
* **Privacy:** Autonomous systems that collect data about individuals raise concerns about privacy and data protection.
* **Employment:** The widespread adoption of autonomous systems could lead to job displacement in certain industries.
* **Accountability:** Who is responsible for the actions of autonomous systems that cause harm?

**The future of autonomous technology:**
Autonomous technology is still in its early stages of development, but it is rapidly advancing with significant investments from governments and private companies. As the technology matures, we can expect to see even more innovative applications and widespread adoption across various sectors of society."
[{2023-12-28 retrieved}]

* McsEngl.Algosoc'att005-technology!⇒Autotech,
* McsEngl.Algosoc'technology!⇒Autotech,
* McsEngl.Autotech!=autonomous-technology,

autonomous-network (link) of Algosoc

relation-to-automated (link) of Algosoc

algorithmic-language of Algosoc

· a-prerequisite of Algosoc.
· a-consistent international-language for humans and machines (lagSngo?), which requires machines to understand our stored knowledge.

* McsEngl.Algolang!=algorithmic-language, {2024-07-21}
* McsEngl.Algosoc'att006-language!⇒Algolang,
* McsEngl.Algosoc'language!⇒Algolang,
* McsEngl.Algolang!=autonomous-language,
* McsEngl.Autolang!⇒Algolang,
* McsEngl.admin-by-algorithm--language!⇒Algolang,
* McsEngl.algorithmic-language!⇒Algolang,
* McsEngl.lagAlgo!⇒Algolang,

lagSinago (link) of Algosoc

algorithmic-science (link) of Algosoc

algorithmic-organization of Algosoc

· a-prerequisite of Algosoc.

">overview of autonomous-organizations:
An autonomous organization refers to an entity that operates independently and self-sufficiently. This concept can be applied in various contexts, including business, technology, and governance. Here are some key aspects:
1. **Self-Governance**: Autonomous organizations are typically self-governed, meaning they have their own set of rules and regulations that guide their operations. This independence allows them to make decisions without external interference.
2. **Technology Integration**: In the context of technology, autonomous organizations might leverage artificial intelligence, machine learning, and blockchain to automate decision-making processes. This can include smart contracts in blockchain technology, where transactions and agreements are automatically executed when certain conditions are met.
3. **Decentralization**: Many autonomous organizations aim for a decentralized structure, which means they do not have a single point of control. This is particularly evident in decentralized autonomous organizations (DAOs) in the blockchain space, where decisions are made collectively by stakeholders rather than a centralized authority.
4. **Innovative Management Structures**: These organizations often experiment with novel management structures, such as flat hierarchies, holacracy, or distributed leadership, to promote agility, flexibility, and employee empowerment.
5. **Financial Independence**: Financial autonomy is a critical aspect, where the organization sustains itself through its own revenue streams or funding mechanisms without relying on external financial support.
6. **Legal Status**: Depending on the jurisdiction, autonomous organizations might have a specific legal status that acknowledges their unique operating model. This is especially relevant for DAOs and similar entities in the crypto space.
7. **Challenges and Risks**: While offering flexibility and innovation, autonomous organizations face challenges like regulatory compliance, ensuring transparency and accountability, and managing complex stakeholder relationships.
8. **Future Trends**: The concept of autonomous organizations is evolving with advancements in technology. They are becoming increasingly significant in discussions about the future of work, governance, and the digital economy.
In summary, autonomous organizations represent a shift towards more self-reliant, technologically driven, and decentralized models of operation, challenging traditional notions of governance and management."
[{2023-12-30 retrieved}]

* McsEngl.Autoozn!=autonomous-organization,
* McsEngl.Algosoc'att007-organization!⇒Autoozn,
* McsEngl.Algosoc'organization!⇒Autoozn,
* McsEngl.admin-by-algorithm--organization!⇒Autoozn,
* McsEngl.autonomous-organization!⇒Autoozn,
* McsEngl.ogzn.010-autonomous!⇒Autoozn,
* McsEngl.ogzn.autonomous!⇒Autoozn,
* McsEngl.ogznAuto!⇒Autoozn,

DAO (link) of Autoozn

info-resource of Autoozn

* {2023-01-14} Minnaar.Joost,

* McsEngl.Autoozn'Infrsc,

evoluting of Autoozn

">evolution of autonomous-organization:
Creating a timeline of autonomous organizations involves looking at the evolution and development of organizations that operate with a significant level of independence or automation. This timeline would typically include milestones in technological development, significant organizations that have pioneered autonomous operations, and key events that have shaped the landscape of such organizations. Here's a general overview:
1. **Early Concepts and Theoretical Foundations (1970s-1990s)**:
- Development of early theories in organizational autonomy.
- Initial experiments with decentralized management structures.
2. **Rise of Digital Technologies and the Internet (1990s-2000s)**:
- Emergence of the internet and advanced computing technologies.
- Initial stages of companies experimenting with digital autonomy.
3. **Advancements in AI and Robotics (2000s-2010s)**:
- Significant advancements in artificial intelligence and robotics.
- The founding of companies focused on autonomous operations in various sectors like manufacturing, logistics, and services.
4. **Expansion of Autonomous Operations (2010s-2020s)**:
- Widespread implementation of AI and machine learning in organizational processes.
- Growth of fully or partially autonomous organizations in sectors like finance, healthcare, and transportation.
5. **Current State and Future Trends (2020s and Beyond)**:
- Integration of advanced AI, including deep learning and neural networks, in decision-making processes.
- Anticipation of new models of autonomous organizations, possibly leveraging blockchain, quantum computing, and other emerging technologies.
This timeline provides a high-level view and may vary depending on specific industries or technological focuses."
[{2023-12-30 retrieved}]

">evolution of autonomous-organization:
The timeline of autonomous organizations starts in the late 1990s with the rise of the internet and the development of smart contracts by Nick Szabo. In 2008, Bitcoin was invented and provided a platform for decentralized autonomous organizations. The first DAO was launched in 2016, and since then there has been a growing interest in this type of organization.
Here is a timeline of some of the major milestones in the history of autonomous organizations:
* **Late 1990s:** Nick Szabo proposes the concept of smart contracts in his paper "Smart Contracts: Building Blocks for Digital Transactions."
* **2008:** Satoshi Nakamoto publishes the white paper for Bitcoin, which establishes the concept of a decentralized blockchain and cryptocurrency.
* **2014:** The concept of decentralized autonomous organizations (DAOs) gains traction as a way to organize businesses without relying on a centralized authority.
* **2016:** The first DAO, called The DAO, is launched on the Ethereum blockchain. The DAO raises over $150 million in an initial coin offering (ICO).
* **2016:** In June, a vulnerability in The DAO's code is exploited in a hack that siphons off $50 million of its funds. The Ethereum community responds by hard-forking the blockchain, which splits the community into two groups: Ethereum and Ethereum Classic.
* **2017:** The DAO concept continues to evolve, and new DAOs are launched for a variety of purposes, including venture capital, governance, and social impact.
* **2020:** The COVID-19 pandemic accelerates the development of DAOs as a way to organize and manage collaborative projects.
* **2021:** The DeFi (decentralized finance) space booms, and DAOs play a key role in the development of new financial applications.
* **2022:** The concept of governance tokens becomes more popular, and DAOs use these tokens to give their members a say in how the organization is run.
* **2023-present:** The growth of DAOs continues, and they are being used for a variety of purposes, including governance, finance, social impact, and even art.
The future of autonomous organizations is bright. As technology advances and more people become comfortable with decentralized systems, we can expect to see even more innovative applications of DAOs in the years to come."
[{2023-12-30 retrieved}]

* McsEngl.Autoozn'evoluting,
* McsEngl.evoluting-of-Autoozn,

algorithmic-city of Algosoc

· an-extended autonomous-organization.

* McsEngl.Autocity,
* McsEngl.Algosoc'city,

governing (link) of DeCity

info-resource of Algosoc

* McsEngl.Algosoc'Infrsc,

* {1993} TOWARDS A NEW SOCIALISM, W. Paul Cockshott and Allin Cottrell,,
* Buterin.Vitalik,,

DOING of Algosoc


* McsEngl.Algosoc'doing,

doing.governing (link)

evoluting of Algosoc

">timeline of autonomous-society:
Sure, here is a timeline of the development of autonomous systems, with a focus on the social implications:
* Norbert Wiener introduces the concept of cybernetics, the study of control and communication systems in animals and machines.
* Alan Turing publishes his paper "Computing Machinery and Intelligence," which introduces the Turing test, a proposed method for determining whether a machine can exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human.
* John McCarthy coins the term "artificial intelligence" (AI) at a conference at Dartmouth College.
* Marvin Minsky and Frank Rosenblatt develop perceptrons, early neural networks that can learn to classify patterns.
* Herbert Simon and Allen Newell create the Logic Theorist, a program that can prove theorems in logic.
* The first AI winter begins, as AI research faces a period of skepticism and funding cuts.
* Joseph Weizenbaum develops ELIZA, a chatbot that simulates conversation with a psychotherapist.
* Marvin Minsky, Terry Winograd, and colleagues develop SHRDLU, a language understanding system that can answer questions about a block world.
* The AI winter ends, and AI research begins to regain funding and momentum.
* John McCarthy and colleagues develop the Lisp programming language, which becomes a popular language for AI research.
* Richard Dawkins introduces the concept of the meme, a unit of cultural transmission that can replicate itself.
* The field of expert systems emerges, with programs like MYCIN and DENDRAL that can provide expert advice in specific domains.
* Rodney Brooks develops subsumption architecture, a control architecture for robots that emphasizes reactive behavior.
* Douglas Hofstadter publishes Gödel, Escher, Bach: An Eternal Golden Braid, which argues that intelligence is a consequence of the ability to create self-referential systems.
* The field of machine learning experiences a renaissance, with the development of new algorithms like backpropagation and support vector machines.
* Deep Blue defeats world chess champion Garry Kasparov, marking a significant milestone in AI.
* The Internet becomes widely available, which opens up new opportunities for AI research and application.
* The development of large language models like GPT-3 and LaMDA leads to significant advances in natural language processing.
* Self-driving cars become a major focus of AI research, with companies like Waymo and Cruise making significant progress.
* AI is increasingly being used to automate tasks in a wide range of industries, from manufacturing to healthcare.
* The field of reinforcement learning experiences a resurgence, with the development of new algorithms that can learn to solve complex tasks through trial and error.
* AI is increasingly being used to analyze and interpret data, leading to new insights in a variety of fields, from medicine to finance.
* AI is being used to develop new forms of creative expression, such as music and art.
* The COVID-19 pandemic accelerates the development and adoption of AI technologies, as they are used to develop new diagnostic tools, track the spread of the virus, and develop vaccines.
* AI is increasingly being used to improve the efficiency and effectiveness of government services.
* AI is being used to address social problems, such as poverty, inequality, and climate change.
**Social implications of autonomous systems:**
* The development of autonomous systems is raising a number of social and ethical concerns, such as job displacement, privacy and surveillance, and the potential for discrimination.
* There is a need for careful consideration of the social and ethical implications of autonomous systems before they are widely deployed.
* Governments, businesses, and civil society organizations need to work together to develop responsible and equitable frameworks for the development and use of autonomous systems.
I hope this timeline is helpful. Please let me know if you have any other questions.

>forcast of autonomous-society:
Predicting the future of autonomous systems and their impact on society is a complex task, as it involves considering various factors and potential scenarios. However, based on current trends and expert opinions, here is a possible forecast of the future of autonomous systems and their impact on society:
**1. Increased Automation and Job Displacement:**
Autonomous systems, particularly in the form of robots and artificial intelligence (AI), are expected to automate a significant portion of tasks currently performed by humans. This will lead to job displacement in industries like manufacturing, transportation, and customer service. However, it will also create new opportunities in areas such as AI development, maintenance, and oversight of autonomous systems.
**2. Transformation of Industries and Work Structures:**
The widespread adoption of autonomous systems will reshape industries and work structures. Organizations will need to adapt to a more dynamic and flexible workforce, requiring new skills and training programs. Collaboration between humans and machines will become increasingly important, with humans taking on higher-level cognitive tasks and supervision, while machines handle repetitive and physical tasks.
**3. Enhanced Productivity and Efficiency:**
Autonomous systems have the potential to significantly boost productivity and efficiency in various sectors. Self-driving vehicles could revolutionize transportation, while automated manufacturing systems could improve production processes. This could lead to increased economic output and overall economic growth.
**4. Rise of AI-Powered Decision-Making:**
AI will play a crucial role in decision-making processes across various domains. From financial investments to medical diagnoses, AI-powered tools and algorithms will help analyze data, identify patterns, and make recommendations. This could lead to more informed and data-driven decision-making.
**5. Ethical Considerations and Regulatory Framework:**
The rapid advancement of autonomous systems raises ethical concerns regarding data privacy, algorithmic bias, and potential misuse. Governments and organizations must develop clear ethical guidelines and regulations to ensure responsible development and deployment of these technologies.
**6. Redefining Human-Machine Interaction:**
The integration of autonomous systems into our daily lives will necessitate a redefinition of the human-machine relationship. We need to establish clear boundaries and guidelines for human control, accountability, and ethical considerations in interactions with AI-powered systems.
**7. Impact on Social Structures and Inequality:**
The widespread adoption of autonomous systems could exacerbate existing social inequalities. Those who can afford access to these technologies may gain a competitive advantage, while those without access could face further marginalization. Governments and social organizations need to address these concerns to promote equitable access and opportunities.
**8. Potential for Conflict and Misuse:**
Autonomous systems could also be used for malicious purposes, such as autonomous weapons, surveillance systems, or cyber-attacks. It is crucial to establish robust cybersecurity measures and international agreements to prevent the misuse of these technologies.
Overall, the future of autonomous systems is full of both promise and challenges. By carefully considering the potential benefits and risks, we can harness the power of these technologies while mitigating their negative impacts. Collaboration among governments, businesses, and civil society organizations will be essential to shape a future where autonomous systems coexist harmoniously with humans and contribute to a better society."
[{2023-12-30 retrieved}]

">forecast of autonomous-society:
Forecasting the development of an autonomous society involves considering several key factors and trends in technology, economics, politics, and social dynamics. Here's a general outlook:
1. **Technological Advancements**: The cornerstone of an autonomous society is the advancement in technologies such as artificial intelligence (AI), robotics, Internet of Things (IoT), and blockchain. AI and robotics are expected to automate a wide range of tasks, from manufacturing to service industries. IoT will enable seamless connectivity and communication between devices, contributing to the efficiency of autonomous systems. Blockchain could offer a secure and decentralized way to manage transactions and data exchanges.
2. **Economic Impacts**: Automation and AI are likely to lead to significant shifts in employment patterns. While some jobs may be lost to automation, new roles, particularly in technology and service sectors, are likely to emerge. There could be increased emphasis on universal basic income (UBI) or similar schemes to address the economic disparities that might arise from widespread automation.
3. **Political and Legal Changes**: Governance structures may need to evolve to regulate and facilitate an autonomous society. This could include new laws and regulations for AI ethics, data privacy, and security. There might be a shift towards more decentralized and participatory forms of governance, possibly leveraging technology like blockchain for transparency and accountability.
4. **Social and Ethical Considerations**: An autonomous society will also bring forth social and ethical challenges, such as the digital divide, privacy concerns, and the ethical use of AI. There could be a greater focus on digital literacy and ethics in education to prepare future generations.
5. **Environmental Impact**: Autonomous technologies have the potential to significantly reduce environmental impact through optimized resource utilization, reduced waste, and efficient energy use. Smart cities, for example, could use autonomous systems for everything from traffic management to waste disposal, thereby reducing carbon footprints.
6. **Healthcare Evolution**: In healthcare, autonomous systems could lead to more personalized and efficient care, with AI assisting in diagnosis, treatment planning, and even surgeries.
7. **Cultural Shifts**: As society becomes more autonomous, there might be a shift in cultural values and norms, particularly regarding work-life balance, the value of human labor, and the role of humans in decision-making processes.
In summary, an autonomous society promises efficiency and innovation but also poses significant challenges that need to be thoughtfully addressed. The transition to such a society will likely be gradual, marked by significant debate and adjustment as we navigate the complex interplay of technology, economics, politics, and ethics."
[{2023-12-30 retrieved}]

* McsEngl.evoluting-of-Algosoc,
* McsEngl.Algosoc'evoluting,

=== McsHitp-creation:
· creation of current concept.

book of Paul-Cockshott (computer scientist) and Allin-Cottrell (economist) about a-computerised planned-economy.

""The world is very advance technologically. Why should egotistical politicians have control, make all the major decisions? Let's put a computer in charge. Then government ministers would be nothing but computer programmers, processing data, with no ego trips, no stupid pride, greed, or chauvinism. It'll all be for the common good."
We hid our tolerant smiles as he unfurled his naive theory, but Karl himself was terribly enthusiastic.
"Of course it's a difficult plan to carry out, so it's advisable that one nation be first to revolutionize itself, and then its neighbors will follow suit until the entire world has adopted the new system. One central computer will control the whole world, and that will be mathematical cosmopolitics""
[{2024-03-30 retrieved} Yossi Ghinsberg, BACK FROM TUICHI, 1985 in Hebrew, 1993 in English, ISBN 0-679-42458-X]
* McsEngl.mathematical-cosmopolitics,

"Project Cybersyn was a Chilean project from 1971 to 1973 during the presidency of Salvador Allende aimed at constructing a distributed decision support system to aid in the management of the national economy. The project consisted of four modules: an economic simulator, custom software to check factory performance, an operations room, and a national network of telex machines that were linked to one mainframe computer."
[{2024-02-21 retrieved}]


* McsEngl.Algosoc'whole-part-tree,

* ... Sympan.



* McsEngl.Algosoc'generic-specific-tree,

* stateless-society,
* classless-society,
* metacapitalist-society,
* knowledge-society,
* info-network-society,
* complex-society,

* ... entity.

* ,


this webpage was-visited times since {2020-10-17}

page-wholepath: / worldviewSngo / dirStn / Algosoc

· this page uses 'locator-names', names that when you find them, you find the-LOCATION of the-concept they denote.
· clicking on the-green-BAR of a-page you have access to the-global--locator-names of my-site.
· use the-prefix 'Algosoc' for sensorial-concepts related to current concept 'society.decentralized.autonomous'.
· TYPE CTRL+F "McsLag4.words-of-concept's-name", to go to the-LOCATION of the-concept.
· a-preview of the-description of a-global-name makes reading fast.

• author: Kaseluris.Nikos.1959
• email:
• edit on github:,
• comments on Disqus,
• twitter: @synagonism,

• version.last.dynamic: ../../dirMcs/dirStn/McsStn000019.last.html,
• version.1-0-0.2021-04-12: (0-2) filMcsSocDa.1-0-0.2021-04-12.html,
• filMcsSocDa.0-1-0.2020-10-17.last.html: draft creation,

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