Machine ethics, also known as Artificial Intelligence (AI) ethics, deals with the ethical considerations surrounding AI and robotics. As these technologies increasingly become an intrinsic part of our everyday lives, machine ethics is gaining significant attention. It helps in addressing ethical dilemmas related to the deployment, utilization, and control of machines, intelligent systems, and AI technologies.

• Ethical Frameworks: Machine ethics revolves around the application of ethical principles and moral standards to AI and autonomous systems. Its main concern is both to avoid harm resulting from the behavior of machines and to promote good.

• Guideline Implementation: Implementing ethical guidelines in the programming and operations of AI systems is a crucial part of machine ethics. This helps ensure the AI behavior aligns with our ethical standards and societal norms.

• Evolving field: Machine ethics is an intriguing and rapidly evolving field that combines the expertise of multiple disciplines including computer science, philosophy, and cognitive science.

• Enhanced accountability: It establishes the responsibility and liability for the behaviors and decisions made by AI and autonomous systems.

Machine ethics is crucial in today's ever-evolving technological landscape. With businesses and industries continually leveraging the benefits of AI and robotics on a wide scale, its importance is heightened. It equips robots and AI systems with the capacity to make ethical decisions autonomously, making technologies more reliable and trustworthy. For AI to gain wider acceptance in society, it is critical that these systems follow ethical norms.

Developing machine ethics involves a multifaceted approach. It requires a deep understanding of ethics from philosophical and practical perspectives, understanding of machine learning and AI, and sensitivity to societal implications of AI technology. Furthermore, the framework needs continual revision and adaptation to embrace the intricacies of moral and ethical decision-making.

• Ethical Consistency: Since ethical guidelines are pre-programmed into systems, machine ethics ensures AI decision-making is consistent with the set rules, unlike humans who may sometimes overlook them.

• Prevent Harm: Ethical considerations can help prevent potential harm caused by machines' unintended actions especially in domains such as autonomous vehicles and healthcare.

• Trustworthy AI: Embedding ethical principles such as honesty, altruism and transparency in AI frameworks, helps build trust among users.

• Scalability: Ethical guidelines can be easily replicated across multiple AI systems, enabling scalability of ethical behavior.

• Challenges in agreement: Consensus on what moral guidelines should be followed by machine systems can be hard to achieve due to ethical diversity.

• Limited adaptability: Preprogrammed ethical guidelines lack flexibility in addressing new or unexpected situations.

• Ethical misuse: Concerns around ethical decisions being manipulated for nefarious purposes pose a serious challenge.

• Complexity of ethical decision-making: Programming a machine to make sound ethical decisions in every possible situation can be an arduous task due to the inherent complexity of ethics.

To sum it up, machine ethics is a budding field that is essential to ensure the responsible development and deployment of AI and autonomous systems. By furnishing AI and robot systems with ethical guidelines, it aspires to make these technologies more beneficial, reliable and trustworthy. It provides a framework that imparts ethical behavior to AI systems thereby reinforcing human trust in these technologies. However, the path to formulating a universally acceptable and effective ethical framework for machines is still under exploration and requires continual research, input from various disciplines and regular assessment.